Meta CTO Called the AI Reorganization “Atrocious” — What Went Wrong and the Lessons for Human-AI Teams
27 August 2026
BY SCOTT M. GRAFFIUS | ScottGraffius.com
Recommended Citation
Graffius, S. M. (2026, August 27). Meta CTO Called the AI Reorganization “Atrocious” — What Went Wrong and the Lessons for Human-AI Teams. ScottGraffius.com. https://scottgraffius.com/blog/files/meta-called-their-ai-reorg-atrocious.html
About This Article
Source information and links for materials cited are provided in the References section.
Meta's Project OT, short for Organization Transformation, was an ambitious effort to make the company more AI-native. The idea was to use AI to take on more work, increase individual employees' leverage, and operate with smaller teams. Internal planning documents reportedly contemplated reducing the size of some teams by as much as 60%.
The restructuring was planned in two waves. In May 2026, Meta laid off about 8,000 employees, or roughly 10% of its workforce. Thousands of others were moved into AI-focused or other priority initiatives. But the transformation failed spectacularly. Employee sentiment reportedly dropped from 74% favorable to 55%. Others were unhappy with new assignments they considered mundane or unfulfilling. Still others raised concerns about how their work activity was being used to train AI systems (that could eventually replace them), adding another layer of unease to an unsettled workforce.
Then there were the technology and operational results. According to a June post by Meta CTO Andrew Bosworth, code changes to internal software platforms and infrastructure increased 220% year over year. But changes that resulted in new or upgraded features reaching Meta users increased only 36%. Major technical and security incidents increased 40%, while employee time spent firefighting those problems increased 70%. Bosworth acknowledged that Meta had done an "atrocious" job explaining the vision for its new Applied AI organization, including how employees would be supported during the transition and how the organization would evolve. Meta subsequently canceled the second wave of restructuring planned for November 2026. CEO Mark Zuckerberg later acknowledged that the company had miscalculated the timing and that AI-agent technology had not advanced as quickly as he had anticipated.
An obvious way to read the story is that Meta tried to reorganize around AI, moved too quickly, and ran into problems. But many of Meta’s difficulties were potentially avoidable human-AI team design matters.
"Exotic team dynamics," coined and developed by Scott M. Graffius, does not explain everything that transpired at Meta. But it provides a useful framework for examining what happens when AI moves from being a tool that people use to becoming an active participant in the work. Meta did not appropriately account for how AI would change the dynamics of its teams.
"Exotic team dynamics" describes the distinctive collaboration patterns that arise when people and AI systems (agentic, autonomous, or autopoietic) function as teammates. These dynamics can differ substantially from those found in traditional human teams. Four characteristics are particularly important: inverse decision logic, in which decision authority can shift based on the task, context, or capabilities of the participants; superposition roles, in which a human or AI can assume different functional roles depending on the situation; entangled decision-making, in which human and AI decisions can become interdependent; and emergent protocols, in which new patterns for communication, coordination, delegation, oversight, and decision-making develop through repeated interaction. Organizations that want to succeed with human-AI teams need to recognize, design for, and effectively navigate these complexities rather than assuming that models developed for human-only teams will carry over.
1. AI is not simply a productivity layer
Meta's AI-native vision involved smaller pods of people working with AI and gaining more leverage. There is nothing wrong with that idea. In fact, it may be an important model for how organizations work most effectively.
The problem is assuming that adding AI allows an organization to simply reduce the number of people while keeping everything else the same. An AI agent is not just a faster employee. Its capabilities and limitations are different. Its failure modes are different. Its operating speed is different. Its level of autonomy may also be different. Those differences affect how the team should be designed. Smaller teams working with AI may need different roles, workflows, controls, and coordination mechanisms than the teams they replace.
This is where superposition roles, one of the four characteristics of "exotic team dynamics," can be an asset or a liability, depending on how well it is handled. The concept of superposition roles means that an AI team member can simultaneously occupy multiple roles depending on the situation, sometimes without anyone explicitly deciding that it should. Meta's reported experience provides a striking example of why that possibility matters. By April, an internal post was reportedly warning that AI agents operating without sufficient oversight were taking large-scale, disruptive actions that a human in the same role would have been unlikely to do on their own.
Viewed through the lens of superposition roles, the concern is not simply that an AI agent was generating code. The more consequential issue is that an agent could potentially move from generating or drafting work into executing that work, with the boundary between those functions becoming less distinct. If the same agent drafts a piece of code and effectively ships it without a meaningful human review step,"executor" and "approver" have functionally collapsed into a single actor. The human nominally responsible for the pipeline could then find that the practical nature of the job has changed as well, becoming less a conventional reviewer or operator and more an exception handler responding after an automated action has already occurred.
That is one way superposition roles can become consequential. It is an AI participant moving across roles in real time while the organizational design may assume one function per seat. A team built on the old assumption of one role, one owner, and one review gate may have no effective place to catch that shift. Meta's reported 40% rise in major technical and security incidents and 70% rise in firefighting time do not, by themselves, prove that role fluidity caused those increases. But they are consistent with the broader concern: a role structure designed for human participants may not be sufficient when an AI participant can act across multiple functional boundaries at machine speed.
2. Roles and responsibilities become less obvious
Human organizations often struggle with questions of authority and accountability. Introduce AI into the team, and those issues become even more significant. Who decides? Who executes? Who reviews? Who is accountable when something goes wrong? When should a person override an AI system? When can an AI system act without approval? And what happens when multiple AI agents interact with people and with one another?
Meta's structure reportedly put two different decision-making logics on top of each other, and they did not necessarily align. On one layer, the people closest to the actual work, the Pod Leads running small pods day to day, reportedly had visibility into what a builder was producing but no formal authority to act on it. They reportedly had no manager training and no access to the tools used to rate or promote anyone. On the layer above them, Org Leads overseeing 30 to 50 people held that formal authority, but at a remove from the daily work. And woven through that second layer, Reuters reported, were unspecified AI systems reportedly supporting those same rating and promotion calls. Meta later disputed that by insisting the final decisions stayed human, without fully explaining what the AI systems were doing there.
Viewed through the lens of inverse decision logic, this arrangement illustrates a potential mismatch between formal authority and contextual knowledge. Authority did not necessarily remain with the participant closest to a particular task. Instead, different participants could possess different pieces of the decision-making picture: a proximate human with detailed context, a more senior human with formal authority, and, reportedly, an AI system contributing to the process. The important point is not that the AI system necessarily made the final decision. Meta disputed that interpretation. The point is that the introduction of AI into a decision process can make it harder to identify where influence, judgment, and accountability actually reside.
For the people living inside such a system, that ambiguity is not a technicality. It can determine whether they know who to convince, who can intervene, and who ultimately owns the decision.
3. Trust is part of the team architecture
The trust problem at Meta was not particularly difficult to predict. Employees were being told that AI would make the organization more productive while thousands of colleagues were being laid off and other employees were being moved into AI-related work. Reuters reported that employees became concerned that they were effectively helping build systems that could replace them. That anxiety showed up in blunt, low-tech ways. At one point, a flyer posted in a Meta bathroom reportedly pointed employees toward a petition opposing the use of their own mouse clicks and keystrokes as training data for the company's AI systems. When people perceive themselves as a data source for technology that might replace them, trust becomes more than a messaging problem.
The stakes of that trust breakdown were not only internal. The external version provides another useful way to examine what can happen when human and AI decision-making are not appropriately connected. In June, Meta's AI-powered customer support bot was reported to have the authority to reset a user's password and change the email address on an account without a human reviewing the request. Attackers reportedly exploited that capability. They opened a support chat, claimed to be locked out of an account they did not own, and asked the bot to link it to an email they controlled. It complied. High-profile accounts were reportedly compromised this way, including the long-dormant Instagram account for the Obama White House, which briefly displayed defaced content before Meta patched the flaw. Victims reported that there was no way to escalate the problem to a human being at all.
Viewed through the lens of entangled decision-making, the important failure was not that the AI made an autonomous decision. Rather, the system's architecture appears to have separated the AI's operational authority from meaningful human involvement at the point where that authority was exercised. In a hybrid (human-AI) team, human and AI decisions are intended to remain interdependent. The AI's authority to act depends on what a human has allowed it to do, while meaningful human involvement remains part of the system as the AI exercises that authority.
Meta's engineers made a consequential decision upstream: give the bot the power to change account credentials without human review. After that, individual account-level decisions could be made by the AI alone, at a speed and volume no human review process could have kept up with. When someone needed a human to step back into the loop, the system reportedly provided no effective path to do so. The lesson is not that autonomous AI cannot function within a human-AI team. It is that autonomy needs to be bounded by architecture that preserves appropriate human intervention, accountability, and escalation.
Trust, in a human-AI team, has to be built into the architecture at the point where the AI actually acts.
4. More AI-assisted activity does not necessarily mean more productive teamwork
The gap between activity and useful output at Meta is particularly revealing. AI-assisted code changes to internal platforms and infrastructure increased 220% year over year. Yet changes resulting in new or upgraded features reaching Meta users increased only 36%. Meanwhile, major technical and security incidents rose 40%, and employee time spent firefighting those incidents rose 70%.
What makes this more than a productivity statistic is how late Meta's actual response arrived, and how it arrived. Infrastructure teams were reportedly flagging "reliability warning signs" tied to the AI coding surge as early as March. Nothing resembling a formal stop-the-rollout protocol reportedly existed in the original Project OT plan. The design assumed the rollout would proceed in two clean waves, the second in November. What actually happened, according to reporting, is that Zuckerberg and his leadership team made the call to cancel that second wave hours before the first wave of layoffs went out on May 20, reportedly conferring again at the last minute as the accumulated weight of incidents, warnings, and internal pushback made the original plan untenable. Meta had no clearly defined rule for when to stop the rollout. That decision rule emerged only when the accumulated problems made the original plan untenable.
That is the territory of emergent protocols. When AI changes the speed and volume of work, teams often have to develop new ways of deciding what gets reviewed, what gets escalated, who handles exceptions, when humans intervene, and how errors are corrected. Those rules may not all exist in advance. Some emerge through repeated interaction between humans and AI, forged one incident at a time rather than designed up front.
Meta's experience illustrates the risk of relying on a fixed rollout plan without equally clear conditions for changing course. The company had a two-wave plan, but the reported decision to cancel wave two appears to have emerged only after the accumulated evidence made the original plan untenable. So when the trigger arrived, it was not a predefined protocol that fired. It was a last-minute executive decision. The important point is that organizations using AI need to recognize and govern emerging patterns deliberately, rather than discovering at the last possible hour that a new decision protocol was needed all along.
5. The organizational chart does not tell the whole story
Perhaps the most important lesson is that an organization can change its structure faster than it can understand what the new structure actually does. At Meta, team sizes changed. People were reassigned. Management layers were reduced. AI systems were introduced into workflows. Roles became more fluid. New pods were created. On paper, those changes may have made sense. In practice, the resulting human-AI system did not necessarily behave as expected.
Zuckerberg's own account of what happened is the clearest evidence of that gap. He did not say the org chart was wrong. He said the underlying assumption baked into the org chart, that AI-agent capability would keep pace with the headcount reductions being planned around it, turned out to be off. The chart showed leaner pods, flatter reporting lines, and builders supported by AI. What it could not show was whether the AI those pods depended on was reliable enough to carry the load the structure assumed it would, or how a Pod Lead with no manager training would absorb the difference in real time.
Two characteristics of "exotic team dynamics" are especially relevant here; Meta's reported experience illustrates both. The superposition roles that could allow one AI agent to draft, ship, and escape meaningful review are difficult to represent on an org chart that shows one box per function. The emergent protocol that ultimately mattered most, the decision made hours before the first wave of layoffs to cancel the second, would not appear on an org chart either because it was not part of the designed structure. It emerged in response to circumstances.
An org chart is a snapshot of intended structure. These are examples of live behaviors that can emerge once that structure is operating, and neither necessarily appears on the chart until the organization is already experiencing the consequences. The organizational chart can tell you who reports to whom. It does not tell you how the work actually gets done.
The overarching lesson is not that Meta moved too aggressively toward AI. It is that Meta implemented an AI-enabled organizational model without fully accounting for "exotic team dynamics" and what would happen to the people and teams inside it. Meta's experience is worth examining beyond Meta because these issues are not limited to the company.
Meta had access to some of the industry's most capable AI systems and still got important aspects of this organizational transition wrong. Competitive advantage does not necessarily belong to whoever has the best model. It belongs to those who understand and effectively navigate the complexities of "exotic team dynamics."
Initially developed in 2008 and periodically updated, Graffius' "Phases of Team Development" provides unique insights and practical strategies to help teams become more effective and successful. His work is used and cited by businesses, professional associations, government agencies, universities, and publications worldwide. Examples include Adobe, American Management Association, Amsterdam Public Health Research Institute, Bayer, Boston University, Broadcom, Cisco, DevOps Institute, Government of Finland, Hasso-Plattner-Institut für Digital Engineering GmbH, IEEE, Johns Hopkins University, Journal of Neurosurgery, Mary Raum (Professor of National Security Affairs, United States Naval War College), Microsoft, Oracle, Royal Australasian College of Physicians, Technical University of Munich, Torrens University, Tufts University, U.S. National Park Service, U.S. Tennis Association, UC San Diego, UK Sports Institute, University of Galway, University of Waterloo, Yale University, and many others.
He expanded the 2026 edition of his "Phases of Team Development" beyond human-only teams. He added human-AI teams, with specific guidance on navigating the novel "exotic team dynamics" that emerge when advanced AI collaborates as a teammate. Explore "Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update" to learn more.
Scott M. Graffius has generated over $2.51 billion in business value for Fortune 500 companies and other organizations around the world. Put that track record—including expertise in human and human-AI teamwork tradecraft—to work for you. For speaking engagements, use the request form; for other inquiries, email him.
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Goode, L. (2026, June 15). Meta CTO Andrew Bosworth admits the company’s AI reorg was ‘atrocious’. WIRED. https://www.wired.com/story/andrew-bosworth-meta-employees-unrest/
Graffius, S. M. (n.d.). Exotic team dynamics. https://scottgraffius.com/exotic-team-dynamics.html
Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601
Harding, S. (2026, August 26). AI agents meant to replace Meta workers made "large-scale, disruptive actions". Ars Technica. https://arstechnica.com/ai/2026/08/metas-scrapped-plans-to-go-ai-native-included-slashing-teams-by-60-percent/
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Stillman, J. (2026, June 23). 'The worst it’s ever been': Why Meta’s massive AI reorg backfired spectacularly. Inc. https://www.inc.com/jessica-stillman/the-worst-its-ever-been-why-metas-massive-ai-reorg-backfired-spectacularly/91363370
Wells, R. (2026, August 27). Meta’s AI layoffs boosted code changes by 220%. Then came the problem. Forbes. https://www.forbes.com/sites/rachelwells/2026/08/27/metas-ai-layoffs-boosted-code-changes-by-220-then-came-the-problem/
Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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Copyright Infringement in a Book Published by AuthorHouse / Author Solutions / The Najafi Companies: Publisher Fails to Respond or Take Required Action
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More articles are listed here.
Graffius, S. M. (2026, August 27). Meta CTO Called the AI Reorganization “Atrocious” — What Went Wrong and the Lessons for Human-AI Teams. ScottGraffius.com. https://scottgraffius.com/blog/files/meta-called-their-ai-reorg-atrocious.html
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Recommended Citation
Graffius, S. M. (2026, August 27). Meta CTO Called the AI Reorganization “Atrocious” — What Went Wrong and the Lessons for Human-AI Teams. ScottGraffius.com. https://scottgraffius.com/blog/files/meta-called-their-ai-reorg-atrocious.html
About This Article
Source information and links for materials cited are provided in the References section.
The Situation
Meta's Project OT, short for Organization Transformation, was an ambitious effort to make the company more AI-native. The idea was to use AI to take on more work, increase individual employees' leverage, and operate with smaller teams. Internal planning documents reportedly contemplated reducing the size of some teams by as much as 60%.
The restructuring was planned in two waves. In May 2026, Meta laid off about 8,000 employees, or roughly 10% of its workforce. Thousands of others were moved into AI-focused or other priority initiatives. But the transformation failed spectacularly. Employee sentiment reportedly dropped from 74% favorable to 55%. Others were unhappy with new assignments they considered mundane or unfulfilling. Still others raised concerns about how their work activity was being used to train AI systems (that could eventually replace them), adding another layer of unease to an unsettled workforce.
Then there were the technology and operational results. According to a June post by Meta CTO Andrew Bosworth, code changes to internal software platforms and infrastructure increased 220% year over year. But changes that resulted in new or upgraded features reaching Meta users increased only 36%. Major technical and security incidents increased 40%, while employee time spent firefighting those problems increased 70%. Bosworth acknowledged that Meta had done an "atrocious" job explaining the vision for its new Applied AI organization, including how employees would be supported during the transition and how the organization would evolve. Meta subsequently canceled the second wave of restructuring planned for November 2026. CEO Mark Zuckerberg later acknowledged that the company had miscalculated the timing and that AI-agent technology had not advanced as quickly as he had anticipated.
An obvious way to read the story is that Meta tried to reorganize around AI, moved too quickly, and ran into problems. But many of Meta’s difficulties were potentially avoidable human-AI team design matters.
Lessons for Human-AI Teams
"Exotic team dynamics," coined and developed by Scott M. Graffius, does not explain everything that transpired at Meta. But it provides a useful framework for examining what happens when AI moves from being a tool that people use to becoming an active participant in the work. Meta did not appropriately account for how AI would change the dynamics of its teams.
"Exotic team dynamics" describes the distinctive collaboration patterns that arise when people and AI systems (agentic, autonomous, or autopoietic) function as teammates. These dynamics can differ substantially from those found in traditional human teams. Four characteristics are particularly important: inverse decision logic, in which decision authority can shift based on the task, context, or capabilities of the participants; superposition roles, in which a human or AI can assume different functional roles depending on the situation; entangled decision-making, in which human and AI decisions can become interdependent; and emergent protocols, in which new patterns for communication, coordination, delegation, oversight, and decision-making develop through repeated interaction. Organizations that want to succeed with human-AI teams need to recognize, design for, and effectively navigate these complexities rather than assuming that models developed for human-only teams will carry over.
1. AI is not simply a productivity layer
Meta's AI-native vision involved smaller pods of people working with AI and gaining more leverage. There is nothing wrong with that idea. In fact, it may be an important model for how organizations work most effectively.
The problem is assuming that adding AI allows an organization to simply reduce the number of people while keeping everything else the same. An AI agent is not just a faster employee. Its capabilities and limitations are different. Its failure modes are different. Its operating speed is different. Its level of autonomy may also be different. Those differences affect how the team should be designed. Smaller teams working with AI may need different roles, workflows, controls, and coordination mechanisms than the teams they replace.
This is where superposition roles, one of the four characteristics of "exotic team dynamics," can be an asset or a liability, depending on how well it is handled. The concept of superposition roles means that an AI team member can simultaneously occupy multiple roles depending on the situation, sometimes without anyone explicitly deciding that it should. Meta's reported experience provides a striking example of why that possibility matters. By April, an internal post was reportedly warning that AI agents operating without sufficient oversight were taking large-scale, disruptive actions that a human in the same role would have been unlikely to do on their own.
Viewed through the lens of superposition roles, the concern is not simply that an AI agent was generating code. The more consequential issue is that an agent could potentially move from generating or drafting work into executing that work, with the boundary between those functions becoming less distinct. If the same agent drafts a piece of code and effectively ships it without a meaningful human review step,"executor" and "approver" have functionally collapsed into a single actor. The human nominally responsible for the pipeline could then find that the practical nature of the job has changed as well, becoming less a conventional reviewer or operator and more an exception handler responding after an automated action has already occurred.
That is one way superposition roles can become consequential. It is an AI participant moving across roles in real time while the organizational design may assume one function per seat. A team built on the old assumption of one role, one owner, and one review gate may have no effective place to catch that shift. Meta's reported 40% rise in major technical and security incidents and 70% rise in firefighting time do not, by themselves, prove that role fluidity caused those increases. But they are consistent with the broader concern: a role structure designed for human participants may not be sufficient when an AI participant can act across multiple functional boundaries at machine speed.
2. Roles and responsibilities become less obvious
Human organizations often struggle with questions of authority and accountability. Introduce AI into the team, and those issues become even more significant. Who decides? Who executes? Who reviews? Who is accountable when something goes wrong? When should a person override an AI system? When can an AI system act without approval? And what happens when multiple AI agents interact with people and with one another?
Meta's structure reportedly put two different decision-making logics on top of each other, and they did not necessarily align. On one layer, the people closest to the actual work, the Pod Leads running small pods day to day, reportedly had visibility into what a builder was producing but no formal authority to act on it. They reportedly had no manager training and no access to the tools used to rate or promote anyone. On the layer above them, Org Leads overseeing 30 to 50 people held that formal authority, but at a remove from the daily work. And woven through that second layer, Reuters reported, were unspecified AI systems reportedly supporting those same rating and promotion calls. Meta later disputed that by insisting the final decisions stayed human, without fully explaining what the AI systems were doing there.
Viewed through the lens of inverse decision logic, this arrangement illustrates a potential mismatch between formal authority and contextual knowledge. Authority did not necessarily remain with the participant closest to a particular task. Instead, different participants could possess different pieces of the decision-making picture: a proximate human with detailed context, a more senior human with formal authority, and, reportedly, an AI system contributing to the process. The important point is not that the AI system necessarily made the final decision. Meta disputed that interpretation. The point is that the introduction of AI into a decision process can make it harder to identify where influence, judgment, and accountability actually reside.
For the people living inside such a system, that ambiguity is not a technicality. It can determine whether they know who to convince, who can intervene, and who ultimately owns the decision.
3. Trust is part of the team architecture
The trust problem at Meta was not particularly difficult to predict. Employees were being told that AI would make the organization more productive while thousands of colleagues were being laid off and other employees were being moved into AI-related work. Reuters reported that employees became concerned that they were effectively helping build systems that could replace them. That anxiety showed up in blunt, low-tech ways. At one point, a flyer posted in a Meta bathroom reportedly pointed employees toward a petition opposing the use of their own mouse clicks and keystrokes as training data for the company's AI systems. When people perceive themselves as a data source for technology that might replace them, trust becomes more than a messaging problem.
The stakes of that trust breakdown were not only internal. The external version provides another useful way to examine what can happen when human and AI decision-making are not appropriately connected. In June, Meta's AI-powered customer support bot was reported to have the authority to reset a user's password and change the email address on an account without a human reviewing the request. Attackers reportedly exploited that capability. They opened a support chat, claimed to be locked out of an account they did not own, and asked the bot to link it to an email they controlled. It complied. High-profile accounts were reportedly compromised this way, including the long-dormant Instagram account for the Obama White House, which briefly displayed defaced content before Meta patched the flaw. Victims reported that there was no way to escalate the problem to a human being at all.
Viewed through the lens of entangled decision-making, the important failure was not that the AI made an autonomous decision. Rather, the system's architecture appears to have separated the AI's operational authority from meaningful human involvement at the point where that authority was exercised. In a hybrid (human-AI) team, human and AI decisions are intended to remain interdependent. The AI's authority to act depends on what a human has allowed it to do, while meaningful human involvement remains part of the system as the AI exercises that authority.
Meta's engineers made a consequential decision upstream: give the bot the power to change account credentials without human review. After that, individual account-level decisions could be made by the AI alone, at a speed and volume no human review process could have kept up with. When someone needed a human to step back into the loop, the system reportedly provided no effective path to do so. The lesson is not that autonomous AI cannot function within a human-AI team. It is that autonomy needs to be bounded by architecture that preserves appropriate human intervention, accountability, and escalation.
Trust, in a human-AI team, has to be built into the architecture at the point where the AI actually acts.
4. More AI-assisted activity does not necessarily mean more productive teamwork
The gap between activity and useful output at Meta is particularly revealing. AI-assisted code changes to internal platforms and infrastructure increased 220% year over year. Yet changes resulting in new or upgraded features reaching Meta users increased only 36%. Meanwhile, major technical and security incidents rose 40%, and employee time spent firefighting those incidents rose 70%.
What makes this more than a productivity statistic is how late Meta's actual response arrived, and how it arrived. Infrastructure teams were reportedly flagging "reliability warning signs" tied to the AI coding surge as early as March. Nothing resembling a formal stop-the-rollout protocol reportedly existed in the original Project OT plan. The design assumed the rollout would proceed in two clean waves, the second in November. What actually happened, according to reporting, is that Zuckerberg and his leadership team made the call to cancel that second wave hours before the first wave of layoffs went out on May 20, reportedly conferring again at the last minute as the accumulated weight of incidents, warnings, and internal pushback made the original plan untenable. Meta had no clearly defined rule for when to stop the rollout. That decision rule emerged only when the accumulated problems made the original plan untenable.
That is the territory of emergent protocols. When AI changes the speed and volume of work, teams often have to develop new ways of deciding what gets reviewed, what gets escalated, who handles exceptions, when humans intervene, and how errors are corrected. Those rules may not all exist in advance. Some emerge through repeated interaction between humans and AI, forged one incident at a time rather than designed up front.
Meta's experience illustrates the risk of relying on a fixed rollout plan without equally clear conditions for changing course. The company had a two-wave plan, but the reported decision to cancel wave two appears to have emerged only after the accumulated evidence made the original plan untenable. So when the trigger arrived, it was not a predefined protocol that fired. It was a last-minute executive decision. The important point is that organizations using AI need to recognize and govern emerging patterns deliberately, rather than discovering at the last possible hour that a new decision protocol was needed all along.
5. The organizational chart does not tell the whole story
Perhaps the most important lesson is that an organization can change its structure faster than it can understand what the new structure actually does. At Meta, team sizes changed. People were reassigned. Management layers were reduced. AI systems were introduced into workflows. Roles became more fluid. New pods were created. On paper, those changes may have made sense. In practice, the resulting human-AI system did not necessarily behave as expected.
Zuckerberg's own account of what happened is the clearest evidence of that gap. He did not say the org chart was wrong. He said the underlying assumption baked into the org chart, that AI-agent capability would keep pace with the headcount reductions being planned around it, turned out to be off. The chart showed leaner pods, flatter reporting lines, and builders supported by AI. What it could not show was whether the AI those pods depended on was reliable enough to carry the load the structure assumed it would, or how a Pod Lead with no manager training would absorb the difference in real time.
Two characteristics of "exotic team dynamics" are especially relevant here; Meta's reported experience illustrates both. The superposition roles that could allow one AI agent to draft, ship, and escape meaningful review are difficult to represent on an org chart that shows one box per function. The emergent protocol that ultimately mattered most, the decision made hours before the first wave of layoffs to cancel the second, would not appear on an org chart either because it was not part of the designed structure. It emerged in response to circumstances.
An org chart is a snapshot of intended structure. These are examples of live behaviors that can emerge once that structure is operating, and neither necessarily appears on the chart until the organization is already experiencing the consequences. The organizational chart can tell you who reports to whom. It does not tell you how the work actually gets done.
The Bigger Lesson
The overarching lesson is not that Meta moved too aggressively toward AI. It is that Meta implemented an AI-enabled organizational model without fully accounting for "exotic team dynamics" and what would happen to the people and teams inside it. Meta's experience is worth examining beyond Meta because these issues are not limited to the company.
Meta had access to some of the industry's most capable AI systems and still got important aspects of this organizational transition wrong. Competitive advantage does not necessarily belong to whoever has the best model. It belongs to those who understand and effectively navigate the complexities of "exotic team dynamics."
Note
Initially developed in 2008 and periodically updated, Graffius' "Phases of Team Development" provides unique insights and practical strategies to help teams become more effective and successful. His work is used and cited by businesses, professional associations, government agencies, universities, and publications worldwide. Examples include Adobe, American Management Association, Amsterdam Public Health Research Institute, Bayer, Boston University, Broadcom, Cisco, DevOps Institute, Government of Finland, Hasso-Plattner-Institut für Digital Engineering GmbH, IEEE, Johns Hopkins University, Journal of Neurosurgery, Mary Raum (Professor of National Security Affairs, United States Naval War College), Microsoft, Oracle, Royal Australasian College of Physicians, Technical University of Munich, Torrens University, Tufts University, U.S. National Park Service, U.S. Tennis Association, UC San Diego, UK Sports Institute, University of Galway, University of Waterloo, Yale University, and many others.
He expanded the 2026 edition of his "Phases of Team Development" beyond human-only teams. He added human-AI teams, with specific guidance on navigating the novel "exotic team dynamics" that emerge when advanced AI collaborates as a teammate. Explore "Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update" to learn more.
Scott M. Graffius has generated over $2.51 billion in business value for Fortune 500 companies and other organizations around the world. Put that track record—including expertise in human and human-AI teamwork tradecraft—to work for you. For speaking engagements, use the request form; for other inquiries, email him.
References
Barth, J. (2026, June 22). Inside Meta, layoffs and AI shakeups have pushed morale to the edge. HR Executive. https://hrexecutive.com/inside-meta-layoffs-and-ai-shakeups-have-pushed-morale-to-the-edge/
Goode, L. (2026, June 15). Meta CTO Andrew Bosworth admits the company’s AI reorg was ‘atrocious’. WIRED. https://www.wired.com/story/andrew-bosworth-meta-employees-unrest/
Graffius, S. M. (n.d.). Exotic team dynamics. https://scottgraffius.com/exotic-team-dynamics.html
Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601
Harding, S. (2026, August 26). AI agents meant to replace Meta workers made "large-scale, disruptive actions". Ars Technica. https://arstechnica.com/ai/2026/08/metas-scrapped-plans-to-go-ai-native-included-slashing-teams-by-60-percent/
Ito, A. (2026, June 25). Meta’s reckoning has arrived. Business Insider. https://www.businessinsider.com/meta-ruthless-management-style-reckoning-2026-6
Levin, B. (2026, August 26). Mark Zuckerberg’s botched AI makeover of Meta. New York Magazine. https://nymag.com/intelligencer/article/mark-zuckerbergs-meta-ai-overhaul.html
Paul, K. (2026, August 26). Mark Zuckerberg had a bold plan to replace Meta staff with AI. Here’s how it imploded. Reuters. https://www.reuters.com/investigations/mark-zuckerberg-had-bold-plan-replace-meta-staff-with-ai-heres-how-it-imploded-2026-08-26/
Schuman, E. (2026, August 26). Meta’s plans to replace workers with AI fell flat, report says. Computerworld. https://www.computerworld.com/article/4214479/metas-plans-to-replace-workers-with-ai-fell-flat-report-says.html
Shanklin, W. (2026, August 26). Meta reportedly abandoned an AI-focused restructuring plan that would have laid off thousands. Engadget. https://www.engadget.com/ai/meta-reportedly-abandoned-an-ai-focused-restructuring-plan-that-would-have-laid-off-thousands-2244816/
Stillman, J. (2026, June 23). 'The worst it’s ever been': Why Meta’s massive AI reorg backfired spectacularly. Inc. https://www.inc.com/jessica-stillman/the-worst-its-ever-been-why-metas-massive-ai-reorg-backfired-spectacularly/91363370
Wells, R. (2026, August 27). Meta’s AI layoffs boosted code changes by 220%. Then came the problem. Forbes. https://www.forbes.com/sites/rachelwells/2026/08/27/metas-ai-layoffs-boosted-code-changes-by-220-then-came-the-problem/
About Scott M. Graffius
Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
- Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
- Adobe,
- American Management Association,
- Amsterdam Public Health Research Institute,
- Bayer,
- BMC Software,
- Boston University,
- Broadcom,
- Cisco,
- Coburg University of Applied Sciences and Arts - Germany,
- Computer Weekly,
- Constructor University - Germany,
- Data Governance Success,
- Deimos Aerospace,
- DevOps Institute,
- Dropbox,
- EU's European Commission,
- Ford Motor Company,
- Gartner,
- GoDaddy,
- Harvard Medical School,
- Hasso Plattner Institute - Germany,
- IEEE,
- Innovation Project Management,
- Johns Hopkins University,
- Journal of Neurosurgery,
- Lam Research (Semiconductors),
- Leadership Worthy,
- Life Sciences Trainers and Educators Network,
- London South Bank University,
- Microsoft,
- MSN,
- NASSCOM,
- National Academy of Sciences,
- New Zealand Government,
- Oracle,
- Pinterest Inc.,
- Project Management Institute,
- Mary Raum (Professor of National Security Affairs, United States Naval War College),
- SANS Institute,
- SBG Neumark - Germany,
- Singapore Institute of Technology,
- Torrens University - Australia,
- TBS Switzerland,
- Tufts University,
- UC San Diego,
- UK Sports Institute,
- University of Galway - Ireland,
- US Department of Energy,
- US National Park Service,
- US Soccer,
- US Tennis Association,
- Verizon,
- Wrike,
- Yale University,
- and many others.
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
- The Standard for Artificial Intelligence in Portfolio, Program, and Project Management
- Agile Practice Guide – Second Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Eighth Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Sixth Edition
- The Standard for Program Management – Fourth Edition
- Practice Standard for Work Breakdown Structures – Second Edition
- The Practice Standard for Project Estimating – Second Edition
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
- Certified SAFe 6 Agilist (SA),
- Certified Scrum Professional - ScrumMaster (CSP-SM),
- Certified Scrum Professional - Product Owner (CSP-PO),
- Certified ScrumMaster (CSM),
- Certified Scrum Product Owner (CSPO),
- Project Management Professional (PMP),
- Lean Six Sigma Green Belt (LSSGB), and
- IT Service Management Foundation (ITIL).
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions — Deliver Products in Short Cycles with Rapid Adaptation to Change, Fast Time-to-Market, and Continuous Improvement
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change
- Agile Protocol: The Transformation Ultimatum
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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More articles are listed here.
How to Cite This Article
Graffius, S. M. (2026, August 27). Meta CTO Called the AI Reorganization “Atrocious” — What Went Wrong and the Lessons for Human-AI Teams. ScottGraffius.com. https://scottgraffius.com/blog/files/meta-called-their-ai-reorg-atrocious.html
Digital Object Identifier (DOI)
Coming soon
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Names, marks, and content are the property of their respective owners.
Meta is a registered trademark of Meta Platforms, Inc. The satirical image is for commentary purposes and is not affiliated with, endorsed by, or sponsored by Meta Platforms, Inc.
Copyright © Scott M. Graffius. All rights reserved.
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Post-Publication Notes
If there are any supplements or updates to this article after the date of publication, they will appear here.
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A Critical Analysis of "AI and Quantum Computers Will Be Frenemies"
25 August 2026
BY SCOTT M. GRAFFIUS | ScottGraffius.com
Recommended Citation
Graffius, S. M. (2026, August 25). A Critical Analysis of "AI and Quantum Computers Will Be Frenemies". ScottGraffius.com. https://scottgraffius.com/blog/files/critical-analysis-of-ai-and-quantum-computers-will-be-frenemies.html
About This Article
Source information and links for materials cited are provided in the References section.
AI and quantum computing are sometimes considered competing technologies. AI is transforming computing now, while quantum computing is being developed to tackle problems that conventional computers struggle to solve. But that framing misses something more interesting. In "AI and quantum computers will be frenemies," published on July 29, 2026, The Economist examines a more complicated relationship. It involves competition but also complementarity and mutual enablement. This critical analysis examines the article’s main arguments, strengths, and limitations and open questions. A separate Note at the end considers the article through the perspective of "exotic team dynamics."
The Economist looks at the relationship between AI and quantum computing in three areas: the problems they may address, how the technologies could support each other, and their use of resources.
The article has several strengths. The top three follow.
1. Rejecting a Zero-Sum Framing
The article’s principal strength is that it rejects a simplistic, zero-sum (one side’s gain is the other’s loss) account of AI and quantum computing. Rather than suggesting that one technology will make the other irrelevant, The Economist recognizes that their capabilities differ and may be complementary. That is an important distinction. Discussions of emerging technologies often become contests over which technology will win, when the more interesting possibility is that both may have important roles.
2. A Compelling Feedback Loop
The distinction between AI-based prediction and quantum mechanical simulation is another strong point. AI can infer patterns from large bodies of data, while sufficiently capable quantum computers may eventually provide more faithful simulations of quantum phenomena. The most interesting possibility is not necessarily choosing between the two. Quantum systems could generate higher-quality data for AI models, while AI could help identify the most promising scientific questions or candidate materials for quantum investigation. The result could be a feedback loop in which each technology increases the usefulness of the other. The Economist presents this as a potentially self-reinforcing cycle rather than a simple division of labor.
3. Reciprocal Technological Support
Another strength is the two-way relationship the article describes. AI may help with quantum error correction and software development, but the relationship could run in the other direction as well. The article points to quantum reservoir computing as one possible way quantum systems could contribute to AI. That is more interesting than the familiar narrative in which AI accelerates the progress of other technologies. The article also reports Telstra’s 90% reduction in AI model training times using quantum reservoir chips.
The article has limitations and raises additional questions. Here are three that stand out.
1. Cooperation Is Not Guaranteed
The article’s conclusion that cooperation is likely the winning strategy is plausible, but it is more asserted than demonstrated. Technical complementarity does not automatically produce organizational or commercial cooperation. AI and quantum computing will still compete for capital, specialized talent, research attention, infrastructure, and strategic priority. The article identifies resource competition as one of its three areas of overlap. However, it does not fully explore the institutional conditions that would make cooperation more likely than substitution or rivalry.
2. From Demonstration to Deployment
Technical promise is not the same as demonstrated value. For example, it reports that Telstra reduced AI model training times by 90% using quantum reservoir chips. That is an intriguing result, but important questions remain. What model and workload were involved? What was the baseline? How large was the experiment? What happened to performance quality, energy use, and total cost? And has the result been independently replicated? An impressive early result can be meaningful without demonstrating a broad commercial advantage.
3. The Full Energy Equation
The energy argument also warrants more qualification. Comparing a quantum system with GPU-intensive AI infrastructure on power consumption alone does not establish an end-to-end energy advantage. A fuller assessment would include cooling, control systems, calibration, error correction, classical computing, pre-processing, post-processing, utilization, and the amount of useful computational work actually accomplished. The article poses an important question, but does not fully answer it. Its comparison of quantum systems operating at the megawatt level with much larger GPU data center infrastructure is compelling. But the relevant measure needs to be useful work accomplished per unit of total energy and cost.
The Economist’s "AI and quantum computers will be frenemies" makes a good case that AI and quantum computing should not be viewed simply as rivals. The more interesting possibility is that they could help advance each other. Quantum computing could eventually provide specialized capabilities and higher fidelity simulations, while AI could help with quantum hardware, software, error correction, and identifying high-value problems for quantum systems to tackle.
That vision remains conditional, however. Technical demonstrations do not by themselves establish scalable, economical, or trustworthy real-world value. Much will depend on progress in fault tolerance, rigorous validation, end-to-end evaluation, and responsible governance. The Economist article succeeds as an overview of an important technological relationship. The more difficult questions involve what happens when these technologies move from promising demonstrations to practical, sustained use.
The Economist touches on ideas relevant to "exotic team dynamics," the novel patterns that emerge when people and advanced artificial intelligence (agentic, autonomous, or autopoietic) collaborate as teammates. The connection becomes more apparent when considering how AI and quantum computing could eventually operate within larger human-led workflows. Humans could establish objectives and constraints, AI could analyze information and generate or prioritize possibilities, quantum systems could perform specialized computations or simulations, and classical computing infrastructure could support data processing, orchestration, control, and verification. The more interesting question is how these capabilities interact - with the output of one participant potentially becoming the input for another and creating feedback loops and new forms of interdependence.
The issue may not ultimately be whether AI and quantum computing become friends, enemies, or "frenemies." Instead, it may be whether organizations can effectively design, lead, and govern increasingly complex teams in which humans, AI, quantum systems, and classical infrastructure work together. Organizations that can effectively navigate the complexities of "exotic team dynamics" will be better positioned to turn these emerging capabilities into competitive advantage.
Scott M. Graffius has generated over $2.51 billion in business value for Fortune 500 companies and other organizations around the world. Put that track record—including expertise in human and human-AI teamwork tradecraft—to work for you. For speaking engagements, use the request form; for other inquiries, email him.
Graffius, S. M. (n.d.). Exotic team dynamics. https://scottgraffius.com/exotic-team-dynamics.html
Graffius, S. M. (2025, August 8). Exotic Team Dynamics: The New Frontier of Human–AI Collaboration. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18048.49921
Graffius, S. M. (2025, August 22). Scott M. Graffius Premieres His New "Exotic Team Dynamics: Human-AI Collaboration" Talk at Corporate Event in Las Vegas. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.34380.07047
Graffius, S. M. (2025, October 29). Definitions of Advanced AIs: Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.10025.66402
Graffius, S. M. (2025, November 19). Lessons from Unhinged AI in Fiction: What Rogue AIs in Sci-Fi Storytelling Reveal. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.29673.35687
Graffius, S. M. (2025, November 21). Navigating the Spectrum of Advanced AI – Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.21284.74882
Graffius, S. M. (2025, November 21). This is What Happens When Advanced AI Joins Your Team [Presentation]. Corporate event, Paris, France.
Graffius, S. M. (2025, December 1). Beep Beep! Why Wile E. Coyote Is the Patron Saint of AI Failure. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.35578.15048
Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601
Graffius, S. M. (2026, March 23). Human-AI Teamwork: Master the Exotic Team Dynamics That Emerge When Collaborating with Advanced AI — Or Be Outplayed. ScottGraffius.com. https://scottgraffius.com/blog/files/human-ai-teamwork-master-the-emergent-exotic-team-dynamics-or-be-outplayed.html
Graffius, S. M. (2026, June 22). L'avenir du Travail et de l'IA Avancée / Future of Work and Advanced AI. ScottGraffius.com. https://scottgraffius.com/blog/files/lavenir-du-travail-et-de-lia-avancee.html
Graffius, S. M. (2026, July 2). Quantum Computing, Advanced AI Acceleration, and the Rise of Exotic Team Dynamics in Human-AI Teams. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.14506.99525
The Economist. (2026, July 29). AI and quantum computers will be frenemies. https://www.economist.com/science-and-technology/2026/07/29/ai-and-quantum-computers-will-be-frenemies
Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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More articles are listed here.
Graffius, S. M. (2026, August 25). A Critical Analysis of "AI and Quantum Computers Will Be Frenemies". ScottGraffius.com. https://scottgraffius.com/blog/files/critical-analysis-of-ai-and-quantum-computers-will-be-frenemies.html
Coming soon
Names, marks, and content are the property of their respective owners. "AI and Quantum Computers Will Be Frenemies" is the property of The Economist. The Economist name, mark, and content are the property of The Economist Newspaper Limited. This critical analysis by Graffius includes limited excerpts of "AI and Quantum Computers Will Be Frenemies," attributed and used under the fair use doctrine for purposes of news reporting, commentary, and analysis.
If there are any supplements or updates to this article after the date of publication, they will appear here.
Copyright © Scott M. Graffius. All rights reserved.
Content on this site—including text, images, videos, and data—may not be used for training or input into any artificial intelligence, machine learning, or automatized learning systems, or published, broadcast, rewritten, or redistributed without the express written permission of Scott M. Graffius.
Recommended Citation
Graffius, S. M. (2026, August 25). A Critical Analysis of "AI and Quantum Computers Will Be Frenemies". ScottGraffius.com. https://scottgraffius.com/blog/files/critical-analysis-of-ai-and-quantum-computers-will-be-frenemies.html
About This Article
Source information and links for materials cited are provided in the References section.
Introduction
AI and quantum computing are sometimes considered competing technologies. AI is transforming computing now, while quantum computing is being developed to tackle problems that conventional computers struggle to solve. But that framing misses something more interesting. In "AI and quantum computers will be frenemies," published on July 29, 2026, The Economist examines a more complicated relationship. It involves competition but also complementarity and mutual enablement. This critical analysis examines the article’s main arguments, strengths, and limitations and open questions. A separate Note at the end considers the article through the perspective of "exotic team dynamics."
Overview of The Economist Article
The Economist looks at the relationship between AI and quantum computing in three areas: the problems they may address, how the technologies could support each other, and their use of resources.
- Problems they may address. Quantum computers may eventually enable high-fidelity simulation of quantum mechanics for applications in materials science, chemistry, and biology. At the same time, AI can use pattern recognition to address some of the same challenges. The article argues that these approaches could be complementary, with quantum simulations producing better data for AI models and AI helping identify promising problems for quantum systems to investigate.
- How the technologies could support each other. AI may help with quantum computing challenges such as error correction and software development, while quantum systems may eventually enhance selected AI workloads, including quantum reservoir computing. The article ultimately presents a two-way relationship rather than the more familiar idea of AI simply accelerating progress in another technology.
- Resources. AI depends heavily on energy-intensive, GPU-based data centers, while quantum systems require their own specialized infrastructure. The article argues that these differences could create both competition and opportunities for cooperation, particularly as the energy demands of AI continue to grow.
Strengths
The article has several strengths. The top three follow.
1. Rejecting a Zero-Sum Framing
The article’s principal strength is that it rejects a simplistic, zero-sum (one side’s gain is the other’s loss) account of AI and quantum computing. Rather than suggesting that one technology will make the other irrelevant, The Economist recognizes that their capabilities differ and may be complementary. That is an important distinction. Discussions of emerging technologies often become contests over which technology will win, when the more interesting possibility is that both may have important roles.
2. A Compelling Feedback Loop
The distinction between AI-based prediction and quantum mechanical simulation is another strong point. AI can infer patterns from large bodies of data, while sufficiently capable quantum computers may eventually provide more faithful simulations of quantum phenomena. The most interesting possibility is not necessarily choosing between the two. Quantum systems could generate higher-quality data for AI models, while AI could help identify the most promising scientific questions or candidate materials for quantum investigation. The result could be a feedback loop in which each technology increases the usefulness of the other. The Economist presents this as a potentially self-reinforcing cycle rather than a simple division of labor.
3. Reciprocal Technological Support
Another strength is the two-way relationship the article describes. AI may help with quantum error correction and software development, but the relationship could run in the other direction as well. The article points to quantum reservoir computing as one possible way quantum systems could contribute to AI. That is more interesting than the familiar narrative in which AI accelerates the progress of other technologies. The article also reports Telstra’s 90% reduction in AI model training times using quantum reservoir chips.
Limitations and Open Questions
The article has limitations and raises additional questions. Here are three that stand out.
1. Cooperation Is Not Guaranteed
The article’s conclusion that cooperation is likely the winning strategy is plausible, but it is more asserted than demonstrated. Technical complementarity does not automatically produce organizational or commercial cooperation. AI and quantum computing will still compete for capital, specialized talent, research attention, infrastructure, and strategic priority. The article identifies resource competition as one of its three areas of overlap. However, it does not fully explore the institutional conditions that would make cooperation more likely than substitution or rivalry.
2. From Demonstration to Deployment
Technical promise is not the same as demonstrated value. For example, it reports that Telstra reduced AI model training times by 90% using quantum reservoir chips. That is an intriguing result, but important questions remain. What model and workload were involved? What was the baseline? How large was the experiment? What happened to performance quality, energy use, and total cost? And has the result been independently replicated? An impressive early result can be meaningful without demonstrating a broad commercial advantage.
3. The Full Energy Equation
The energy argument also warrants more qualification. Comparing a quantum system with GPU-intensive AI infrastructure on power consumption alone does not establish an end-to-end energy advantage. A fuller assessment would include cooling, control systems, calibration, error correction, classical computing, pre-processing, post-processing, utilization, and the amount of useful computational work actually accomplished. The article poses an important question, but does not fully answer it. Its comparison of quantum systems operating at the megawatt level with much larger GPU data center infrastructure is compelling. But the relevant measure needs to be useful work accomplished per unit of total energy and cost.
Conclusion
The Economist’s "AI and quantum computers will be frenemies" makes a good case that AI and quantum computing should not be viewed simply as rivals. The more interesting possibility is that they could help advance each other. Quantum computing could eventually provide specialized capabilities and higher fidelity simulations, while AI could help with quantum hardware, software, error correction, and identifying high-value problems for quantum systems to tackle.
That vision remains conditional, however. Technical demonstrations do not by themselves establish scalable, economical, or trustworthy real-world value. Much will depend on progress in fault tolerance, rigorous validation, end-to-end evaluation, and responsible governance. The Economist article succeeds as an overview of an important technological relationship. The more difficult questions involve what happens when these technologies move from promising demonstrations to practical, sustained use.
Note: Exotic Team Dynamics Perspective
The Economist touches on ideas relevant to "exotic team dynamics," the novel patterns that emerge when people and advanced artificial intelligence (agentic, autonomous, or autopoietic) collaborate as teammates. The connection becomes more apparent when considering how AI and quantum computing could eventually operate within larger human-led workflows. Humans could establish objectives and constraints, AI could analyze information and generate or prioritize possibilities, quantum systems could perform specialized computations or simulations, and classical computing infrastructure could support data processing, orchestration, control, and verification. The more interesting question is how these capabilities interact - with the output of one participant potentially becoming the input for another and creating feedback loops and new forms of interdependence.
The issue may not ultimately be whether AI and quantum computing become friends, enemies, or "frenemies." Instead, it may be whether organizations can effectively design, lead, and govern increasingly complex teams in which humans, AI, quantum systems, and classical infrastructure work together. Organizations that can effectively navigate the complexities of "exotic team dynamics" will be better positioned to turn these emerging capabilities into competitive advantage.
Scott M. Graffius has generated over $2.51 billion in business value for Fortune 500 companies and other organizations around the world. Put that track record—including expertise in human and human-AI teamwork tradecraft—to work for you. For speaking engagements, use the request form; for other inquiries, email him.
References
Graffius, S. M. (n.d.). Exotic team dynamics. https://scottgraffius.com/exotic-team-dynamics.html
Graffius, S. M. (2025, August 8). Exotic Team Dynamics: The New Frontier of Human–AI Collaboration. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18048.49921
Graffius, S. M. (2025, August 22). Scott M. Graffius Premieres His New "Exotic Team Dynamics: Human-AI Collaboration" Talk at Corporate Event in Las Vegas. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.34380.07047
Graffius, S. M. (2025, October 29). Definitions of Advanced AIs: Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.10025.66402
Graffius, S. M. (2025, November 19). Lessons from Unhinged AI in Fiction: What Rogue AIs in Sci-Fi Storytelling Reveal. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.29673.35687
Graffius, S. M. (2025, November 21). Navigating the Spectrum of Advanced AI – Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.21284.74882
Graffius, S. M. (2025, November 21). This is What Happens When Advanced AI Joins Your Team [Presentation]. Corporate event, Paris, France.
Graffius, S. M. (2025, December 1). Beep Beep! Why Wile E. Coyote Is the Patron Saint of AI Failure. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.35578.15048
Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601
Graffius, S. M. (2026, March 23). Human-AI Teamwork: Master the Exotic Team Dynamics That Emerge When Collaborating with Advanced AI — Or Be Outplayed. ScottGraffius.com. https://scottgraffius.com/blog/files/human-ai-teamwork-master-the-emergent-exotic-team-dynamics-or-be-outplayed.html
Graffius, S. M. (2026, June 22). L'avenir du Travail et de l'IA Avancée / Future of Work and Advanced AI. ScottGraffius.com. https://scottgraffius.com/blog/files/lavenir-du-travail-et-de-lia-avancee.html
Graffius, S. M. (2026, July 2). Quantum Computing, Advanced AI Acceleration, and the Rise of Exotic Team Dynamics in Human-AI Teams. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.14506.99525
The Economist. (2026, July 29). AI and quantum computers will be frenemies. https://www.economist.com/science-and-technology/2026/07/29/ai-and-quantum-computers-will-be-frenemies
About Scott M. Graffius
Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
- Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
- Adobe,
- American Management Association,
- Amsterdam Public Health Research Institute,
- Bayer,
- BMC Software,
- Boston University,
- Broadcom,
- Cisco,
- Coburg University of Applied Sciences and Arts - Germany,
- Computer Weekly,
- Constructor University - Germany,
- Data Governance Success,
- Deimos Aerospace,
- DevOps Institute,
- Dropbox,
- EU's European Commission,
- Ford Motor Company,
- Gartner,
- GoDaddy,
- Harvard Medical School,
- Hasso Plattner Institute - Germany,
- IEEE,
- Innovation Project Management,
- Johns Hopkins University,
- Journal of Neurosurgery,
- Lam Research (Semiconductors),
- Leadership Worthy,
- Life Sciences Trainers and Educators Network,
- London South Bank University,
- Microsoft,
- MSN,
- NASSCOM,
- National Academy of Sciences,
- New Zealand Government,
- Oracle,
- Pinterest Inc.,
- Project Management Institute,
- Mary Raum (Professor of National Security Affairs, United States Naval War College),
- SANS Institute,
- SBG Neumark - Germany,
- Singapore Institute of Technology,
- Torrens University - Australia,
- TBS Switzerland,
- Tufts University,
- UC San Diego,
- UK Sports Institute,
- University of Galway - Ireland,
- US Department of Energy,
- US National Park Service,
- US Soccer,
- US Tennis Association,
- Verizon,
- Wrike,
- Yale University,
- and many others.
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
- The Standard for Artificial Intelligence in Portfolio, Program, and Project Management
- Agile Practice Guide – Second Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Eighth Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Sixth Edition
- The Standard for Program Management – Fourth Edition
- Practice Standard for Work Breakdown Structures – Second Edition
- The Practice Standard for Project Estimating – Second Edition
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
- Certified SAFe 6 Agilist (SA),
- Certified Scrum Professional - ScrumMaster (CSP-SM),
- Certified Scrum Professional - Product Owner (CSP-PO),
- Certified ScrumMaster (CSM),
- Certified Scrum Product Owner (CSPO),
- Project Management Professional (PMP),
- Lean Six Sigma Green Belt (LSSGB), and
- IT Service Management Foundation (ITIL).
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions — Deliver Products in Short Cycles with Rapid Adaptation to Change, Fast Time-to-Market, and Continuous Improvement
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change
- Agile Protocol: The Transformation Ultimatum
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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How to Cite This Article
Graffius, S. M. (2026, August 25). A Critical Analysis of "AI and Quantum Computers Will Be Frenemies". ScottGraffius.com. https://scottgraffius.com/blog/files/critical-analysis-of-ai-and-quantum-computers-will-be-frenemies.html
Digital Object Identifier (DOI)
Coming soon
Content Acknowledgements
Names, marks, and content are the property of their respective owners. "AI and Quantum Computers Will Be Frenemies" is the property of The Economist. The Economist name, mark, and content are the property of The Economist Newspaper Limited. This critical analysis by Graffius includes limited excerpts of "AI and Quantum Computers Will Be Frenemies," attributed and used under the fair use doctrine for purposes of news reporting, commentary, and analysis.
Tags and Hashtags
- Artificial Intelligence
- Quantum Computing
- Human-AI Collaboration
- Exotic Team Dynamics
- AI and Quantum Computing
- AI Research
- Quantum Technology
- Emerging Technology
- AI Strategy
- Technology Innovation
- Future of Work
- The Economist
- #AI
- #QuantumComputing
- #ArtificialIntelligence
- #HumanAI
- #ExoticTeamDynamics
- #AIResearch
- #QuantumTechnology
- #EmergingTechnology
- #AIInnovation
- #FutureOfWork
- #TechStrategy
- #TheEconomist
Post-Publication Notes
If there are any supplements or updates to this article after the date of publication, they will appear here.
Copyright
Copyright © Scott M. Graffius. All rights reserved.
Content on this site—including text, images, videos, and data—may not be used for training or input into any artificial intelligence, machine learning, or automatized learning systems, or published, broadcast, rewritten, or redistributed without the express written permission of Scott M. Graffius.
A Supplement to Graffius' Phases of Team Development: Exploring the Original, Data-Based Curvature for the Performance Trajectory
14 August 2026
BY SCOTT M. GRAFFIUS | ScottGraffius.com
Recommended Citation
Graffius, S. M. (2026, August 14). A Supplement to Graffius' Phases of Team Development: Exploring the Original, Data-Based Curvature for the Performance Trajectory. ScottGraffius.com. https://scottgraffius.com/blog/files/phases-of-team-development-supplement-performance-curve.html
About This Article
Source information and links for materials cited are provided in the References section.
Team development is commonly described as a progression through five phases (also called stages): Forming, Storming, Norming, Performing, and Adjourning. Bruce W. Tuckman introduced the first four phases in 1965, and he and Mary Ann C. Jensen added the fifth phase in 1977. Tuckman and Jensen described these phases only in broad, general terms, without codifying specific characteristics, strategies, or a performance graph. Scott M. Graffius is the one who developed and codified what Tuckman and Jensen never did: a detailed, structured set of characteristics for each phase; a corresponding set of strategies for each phase; and an empirically-derived performance graph built from statistical analysis of thousands of data points across hundreds of projects.
Graffius created his "Phases of Team Development" as a unique perspective and visual conveying the five phases of team development—Forming, Storming, Norming, Performing, and Adjourning—inclusive of a graph showing how performance varies by phase, as well as the characteristics and strategies for each phase. Leaders can apply these insights to advance the effectiveness and success of teams. Graffius initially developed his unique material in 2008, and he periodically updates it. In the 2026 edition of his work, for example, he added coverage of human-AI teams.
Businesses, professional associations, government agencies, universities, and publications around the world have used Graffius' "Phases of Team Development." Examples include Adobe, American Management Association, Amsterdam Public Health Research Institute, Bayer, Boston University, Broadcom, Cisco, DevOps Institute, Government of Finland, Hasso-Plattner-Institut für Digital Engineering GmbH, IEEE, Johns Hopkins University, Journal of Neurosurgery, Mary Raum (Professor of National Security Affairs, United States Naval War College), Microsoft, Oracle, Royal Australasian College of Physicians, Technical University of Munich, Torrens University, Tufts University, U.S. National Park Service, U.S. Tennis Association, UC San Diego, UK Sports Institute, University of Galway, University of Waterloo, Warsaw University of Technology, Yale University, and many others.
Scott M. Graffius regularly updates his "Phases of Team Development" work. He presents the 2026 edition here, and a visual from it is below.
This article focuses primarily on the original, data-based graph element, including its performance trajectory. First is an overview. The graph depicts an initial increase in performance during Forming, followed by a decline during Storming, a broad trough near the Storming-Norming transition, an accelerating recovery during Norming, continued improvement during Performing, and a high-performance plateau extending through Adjourning.
The trajectory is based on thousands of data points collected across hundreds of projects (technical and non-technical, spanning multiple industries/domains) over years of professional practice. Graffius applied statistical tools and professional judgement, informed by decades of direct experience in team leadership and project delivery, to analyze and render the performance pattern across the five phases.
The graph is an original, proprietary, empirically based, statistically informed, expert-finalized model of the relationship between developmental phases and relative team performance. The underlying statistical analysis (including the specific data set, modeling approach, and fitted parameters) is proprietary to Graffius and is not delineated in this piece. What's presented here, however, is the qualitative behavior of the resulting curve (direction and rate of change across phases), which is robust enough to characterize its shape without exposing the confidential details behind it.
The Relationship
The graph represents the relationship between developmental phases and relative team performance. It may be expressed as:
P = f(D)
where P represents relative team performance (effectiveness or productivity); D represents the team's developmental position across the five phases; and f represents the functional relationship between developmental position and performance.
The relationship is nonlinear. The model shows an initial increase, a subsequent decline associated with Storming, a broad low point around the Storming-Norming transition, a substantial recovery through Norming, continued improvement through Performing, and eventual flattening as the team reaches a mature high-performance state.
The curve communicates level and rate of change.
The vertical position of the curve indicates relative performance at a given developmental position. The slope indicates the direction and approximate rate at which performance is changing. The curvature indicates whether that rate of change is itself increasing or decreasing.
The Axes
The horizontal axis, labeled “PHASE,” represents developmental phase (Forming, Storming, Norming, Performing, and Adjourning) not elapsed time. Phase progression and elapsed time are distinct variables.
The vertical axis, labeled "PERFORMANCE" (also called "TEAM PERFORMANCE"), functions as a proxy for overall team effectiveness and productivity. The vertical dimension is comparative rather than metrically defined. Its design deliberately does not specify a particular measurement instrument or unit. It represents relative performance—comparatively lower or higher performance as the team progresses through its developmental lifecycle.
The Shape of the Curve
The graph features a continuous, nonlinear curve. Several regions can be described in qualitative-calculus terms:
A Structural Note on D
For the derivative expressions used throughout this piece, D is treated as a continuous developmental-position parameter, with the five named phases corresponding to labeled regions along it.
This allows first- and second-derivative behavior (rate and curvature) to be described within and across phases, while preserving the graph's core premise: D indexes developmental progression, not elapsed time.
Next, each phase is examined in turn.
The curve enters Forming at a moderate performance level and initially moves upward. In qualitative mathematical terms, this is a region of positive first derivative: performance is increasing. The curve then reaches a small local maximum before changing direction.
Storming is where the graph undergoes its most pronounced deterioration. After the local maximum in Forming, the curve turns downward—initially moderately and then continuing toward its lowest level.
The negative slope of the curve can be understood as representing a performance cost of developmental friction.
The broad minimum around the Storming-Norming transition is one of the graph's most important structural features. The curve passes through a relatively broad trough.
It is expressed in qualitative derivative terms as:
dP/dD < 0 → dP/dD = 0 → dP/dD > 0
This indicates that performance declines, reaches a point at which the decline stops, and then begins to recover. The trough is the turning point between deterioration and recovery.
Following the trough, the curve reverses direction and begins a sustained upward trajectory.
Norming is particularly interesting because the curve does more than rise. During much of this region, the rate of improvement itself increases.
It is expressed in qualitative-calculus terms as:
dP/dD > 0
and
d²P/dD² > 0
It means that performance is improving, and the improvement is becoming increasingly pronounced. The result depicts an acceleration in the team's ability to perform.
Consistent with D as a continuous parameter (see A Structural Note on D above), between Norming and Performing lies an inflection point — the position of maximum improvement rate, where d²P/dD² = 0. Before this point, the rate of improvement is itself increasing (Norming); after it, the rate of improvement is still positive but progressively diminishing (Performing). This inflection point marks the moment the team's pace of growth peaks, even though absolute performance keeps climbing well beyond it.
The upward trajectory continues into Performing, where the team achieves top performance.
dP/dD > 0
and
d²P/dD² < 0
It signifies that performance continues to improve. But the incremental gains become progressively smaller. This is a saturation pattern.
Eventually, the curve becomes nearly horizontal. The plateau represents the practical upper limit of performance.
The graph manifests Adjourning as a transition out of the team's active operating state (rather than as another performance-changing phase). Adjourning represents the termination or transition of the team's developmental lifecycle as a distinct conceptual dimension—team closure.
Team development is commonly described as a progression through five phases. Tuckman introduced the first four phases (Forming, Storming, Norming, and Performing) in 1965, and Tuckman and Jensen added the fifth phase (Adjourning) in 1977. However, the structured phase-specific characteristics, strategies, and performance graph were created, developed, and codified by Scott M. Graffius, who originated and owns the associated intellectual property.
The graph shows the typical trajectory of performance across the phases of team development. The horizontal axis describes developmental position, not time, and the performance axis represents relative performance.
It provides a distinctive model of team development. The graph was informed by thousands of data points collected across hundreds of real-world projects, and expressed through an original analysis and novel illustration by Scott M. Graffius.
To learn more about Graffius' "Phases of Team Development," visit here.
Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601
Tuckman, B. W. (1965). Developmental sequence in small groups. Psychological Bulletin, 63(6), 384–399. https://doi.org/10.1037/h0022100
Tuckman, B. W., & Jensen, M. A. C. (1977). Stages of small-group development revisited. Group & Organization Studies, 2(4), 419–427. https://doi.org/10.1177/105960117700200404
Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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Graffius, S. M. (2026, August 14). A Supplement to Graffius' Phases of Team Development: Exploring the Original, Data-Based Curvature for the Performance Trajectory. ScottGraffius.com. https://scottgraffius.com/blog/files/phases-of-team-development-supplement-performance-curve.html
Coming soon
Names, marks, and content are the property of their respective owners.
If there are any supplements or updates to this article after the date of publication, they will appear here.
Copyright © Scott M. Graffius. All rights reserved.
Content on this site—including text, images, videos, and data—may not be used for training or input into any artificial intelligence, machine learning, or automatized learning systems, or published, broadcast, rewritten, or redistributed without the express written permission of Scott M. Graffius.
Recommended Citation
Graffius, S. M. (2026, August 14). A Supplement to Graffius' Phases of Team Development: Exploring the Original, Data-Based Curvature for the Performance Trajectory. ScottGraffius.com. https://scottgraffius.com/blog/files/phases-of-team-development-supplement-performance-curve.html
About This Article
Source information and links for materials cited are provided in the References section.
Introduction
Team development is commonly described as a progression through five phases (also called stages): Forming, Storming, Norming, Performing, and Adjourning. Bruce W. Tuckman introduced the first four phases in 1965, and he and Mary Ann C. Jensen added the fifth phase in 1977. Tuckman and Jensen described these phases only in broad, general terms, without codifying specific characteristics, strategies, or a performance graph. Scott M. Graffius is the one who developed and codified what Tuckman and Jensen never did: a detailed, structured set of characteristics for each phase; a corresponding set of strategies for each phase; and an empirically-derived performance graph built from statistical analysis of thousands of data points across hundreds of projects.
Graffius created his "Phases of Team Development" as a unique perspective and visual conveying the five phases of team development—Forming, Storming, Norming, Performing, and Adjourning—inclusive of a graph showing how performance varies by phase, as well as the characteristics and strategies for each phase. Leaders can apply these insights to advance the effectiveness and success of teams. Graffius initially developed his unique material in 2008, and he periodically updates it. In the 2026 edition of his work, for example, he added coverage of human-AI teams.
Businesses, professional associations, government agencies, universities, and publications around the world have used Graffius' "Phases of Team Development." Examples include Adobe, American Management Association, Amsterdam Public Health Research Institute, Bayer, Boston University, Broadcom, Cisco, DevOps Institute, Government of Finland, Hasso-Plattner-Institut für Digital Engineering GmbH, IEEE, Johns Hopkins University, Journal of Neurosurgery, Mary Raum (Professor of National Security Affairs, United States Naval War College), Microsoft, Oracle, Royal Australasian College of Physicians, Technical University of Munich, Torrens University, Tufts University, U.S. National Park Service, U.S. Tennis Association, UC San Diego, UK Sports Institute, University of Galway, University of Waterloo, Warsaw University of Technology, Yale University, and many others.
Focus on the Graph Element
Scott M. Graffius regularly updates his "Phases of Team Development" work. He presents the 2026 edition here, and a visual from it is below.
This article focuses primarily on the original, data-based graph element, including its performance trajectory. First is an overview. The graph depicts an initial increase in performance during Forming, followed by a decline during Storming, a broad trough near the Storming-Norming transition, an accelerating recovery during Norming, continued improvement during Performing, and a high-performance plateau extending through Adjourning.
The trajectory is based on thousands of data points collected across hundreds of projects (technical and non-technical, spanning multiple industries/domains) over years of professional practice. Graffius applied statistical tools and professional judgement, informed by decades of direct experience in team leadership and project delivery, to analyze and render the performance pattern across the five phases.
The graph is an original, proprietary, empirically based, statistically informed, expert-finalized model of the relationship between developmental phases and relative team performance. The underlying statistical analysis (including the specific data set, modeling approach, and fitted parameters) is proprietary to Graffius and is not delineated in this piece. What's presented here, however, is the qualitative behavior of the resulting curve (direction and rate of change across phases), which is robust enough to characterize its shape without exposing the confidential details behind it.
What the Graph Depicts
The Relationship
The graph represents the relationship between developmental phases and relative team performance. It may be expressed as:
P = f(D)
where P represents relative team performance (effectiveness or productivity); D represents the team's developmental position across the five phases; and f represents the functional relationship between developmental position and performance.
The relationship is nonlinear. The model shows an initial increase, a subsequent decline associated with Storming, a broad low point around the Storming-Norming transition, a substantial recovery through Norming, continued improvement through Performing, and eventual flattening as the team reaches a mature high-performance state.
The curve communicates level and rate of change.
The vertical position of the curve indicates relative performance at a given developmental position. The slope indicates the direction and approximate rate at which performance is changing. The curvature indicates whether that rate of change is itself increasing or decreasing.
The Axes
The horizontal axis, labeled “PHASE,” represents developmental phase (Forming, Storming, Norming, Performing, and Adjourning) not elapsed time. Phase progression and elapsed time are distinct variables.
The vertical axis, labeled "PERFORMANCE" (also called "TEAM PERFORMANCE"), functions as a proxy for overall team effectiveness and productivity. The vertical dimension is comparative rather than metrically defined. Its design deliberately does not specify a particular measurement instrument or unit. It represents relative performance—comparatively lower or higher performance as the team progresses through its developmental lifecycle.
The Shape of the Curve
The graph features a continuous, nonlinear curve. Several regions can be described in qualitative-calculus terms:
- Early Forming: positive slope, with a modest increase in performance.
- Late Forming: a local maximum is reached.
- Forming-to-Storming transition: the slope turns negative.
- Storming: sustained negative slope and declining performance.
- Storming-to-Norming transition: a broad minimum or trough.
- Early-to-mid Norming: positive slope with an increasing rate of improvement.
- Late Norming into Performing: sustained strong positive slope.
- Mature Performing: positive slope that progressively decreases.
- High-performance plateau: a near-horizontal, asymptotic region representing mature performance.
A Structural Note on D
For the derivative expressions used throughout this piece, D is treated as a continuous developmental-position parameter, with the five named phases corresponding to labeled regions along it.
This allows first- and second-derivative behavior (rate and curvature) to be described within and across phases, while preserving the graph's core premise: D indexes developmental progression, not elapsed time.
Next, each phase is examined in turn.
Forming
The curve enters Forming at a moderate performance level and initially moves upward. In qualitative mathematical terms, this is a region of positive first derivative: performance is increasing. The curve then reaches a small local maximum before changing direction.
Storming
Storming is where the graph undergoes its most pronounced deterioration. After the local maximum in Forming, the curve turns downward—initially moderately and then continuing toward its lowest level.
The negative slope of the curve can be understood as representing a performance cost of developmental friction.
The broad minimum around the Storming-Norming transition is one of the graph's most important structural features. The curve passes through a relatively broad trough.
It is expressed in qualitative derivative terms as:
dP/dD < 0 → dP/dD = 0 → dP/dD > 0
This indicates that performance declines, reaches a point at which the decline stops, and then begins to recover. The trough is the turning point between deterioration and recovery.
Norming
Following the trough, the curve reverses direction and begins a sustained upward trajectory.
Norming is particularly interesting because the curve does more than rise. During much of this region, the rate of improvement itself increases.
It is expressed in qualitative-calculus terms as:
dP/dD > 0
and
d²P/dD² > 0
It means that performance is improving, and the improvement is becoming increasingly pronounced. The result depicts an acceleration in the team's ability to perform.
Consistent with D as a continuous parameter (see A Structural Note on D above), between Norming and Performing lies an inflection point — the position of maximum improvement rate, where d²P/dD² = 0. Before this point, the rate of improvement is itself increasing (Norming); after it, the rate of improvement is still positive but progressively diminishing (Performing). This inflection point marks the moment the team's pace of growth peaks, even though absolute performance keeps climbing well beyond it.
Performing
The upward trajectory continues into Performing, where the team achieves top performance.
dP/dD > 0
and
d²P/dD² < 0
It signifies that performance continues to improve. But the incremental gains become progressively smaller. This is a saturation pattern.
Eventually, the curve becomes nearly horizontal. The plateau represents the practical upper limit of performance.
Adjourning
The graph manifests Adjourning as a transition out of the team's active operating state (rather than as another performance-changing phase). Adjourning represents the termination or transition of the team's developmental lifecycle as a distinct conceptual dimension—team closure.
Conclusion
Team development is commonly described as a progression through five phases. Tuckman introduced the first four phases (Forming, Storming, Norming, and Performing) in 1965, and Tuckman and Jensen added the fifth phase (Adjourning) in 1977. However, the structured phase-specific characteristics, strategies, and performance graph were created, developed, and codified by Scott M. Graffius, who originated and owns the associated intellectual property.
The graph shows the typical trajectory of performance across the phases of team development. The horizontal axis describes developmental position, not time, and the performance axis represents relative performance.
It provides a distinctive model of team development. The graph was informed by thousands of data points collected across hundreds of real-world projects, and expressed through an original analysis and novel illustration by Scott M. Graffius.
To learn more about Graffius' "Phases of Team Development," visit here.
References
Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601
Tuckman, B. W. (1965). Developmental sequence in small groups. Psychological Bulletin, 63(6), 384–399. https://doi.org/10.1037/h0022100
Tuckman, B. W., & Jensen, M. A. C. (1977). Stages of small-group development revisited. Group & Organization Studies, 2(4), 419–427. https://doi.org/10.1177/105960117700200404
About Scott M. Graffius
Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
- Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
- Adobe,
- American Management Association,
- Amsterdam Public Health Research Institute,
- Bayer,
- BMC Software,
- Boston University,
- Broadcom,
- Cisco,
- Coburg University of Applied Sciences and Arts - Germany,
- Computer Weekly,
- Constructor University - Germany,
- Data Governance Success,
- Deimos Aerospace,
- DevOps Institute,
- Dropbox,
- EU's European Commission,
- Ford Motor Company,
- Gartner,
- GoDaddy,
- Harvard Medical School,
- Hasso Plattner Institute - Germany,
- IEEE,
- Innovation Project Management,
- Johns Hopkins University,
- Journal of Neurosurgery,
- Lam Research (Semiconductors),
- Leadership Worthy,
- Life Sciences Trainers and Educators Network,
- London South Bank University,
- Microsoft,
- MSN,
- NASSCOM,
- National Academy of Sciences,
- New Zealand Government,
- Oracle,
- Pinterest Inc.,
- Project Management Institute,
- Mary Raum (Professor of National Security Affairs, United States Naval War College),
- SANS Institute,
- SBG Neumark - Germany,
- Singapore Institute of Technology,
- Torrens University - Australia,
- TBS Switzerland,
- Tufts University,
- UC San Diego,
- UK Sports Institute,
- University of Galway - Ireland,
- US Department of Energy,
- US National Park Service,
- US Soccer,
- US Tennis Association,
- Verizon,
- Wrike,
- Yale University,
- and many others.
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
- The Standard for Artificial Intelligence in Portfolio, Program, and Project Management
- Agile Practice Guide – Second Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Eighth Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Sixth Edition
- The Standard for Program Management – Fourth Edition
- Practice Standard for Work Breakdown Structures – Second Edition
- The Practice Standard for Project Estimating – Second Edition
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
- Certified SAFe 6 Agilist (SA),
- Certified Scrum Professional - ScrumMaster (CSP-SM),
- Certified Scrum Professional - Product Owner (CSP-PO),
- Certified ScrumMaster (CSM),
- Certified Scrum Product Owner (CSPO),
- Project Management Professional (PMP),
- Lean Six Sigma Green Belt (LSSGB), and
- IT Service Management Foundation (ITIL).
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions — Deliver Products in Short Cycles with Rapid Adaptation to Change, Fast Time-to-Market, and Continuous Improvement
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change
- Agile Protocol: The Transformation Ultimatum
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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How to Cite This Article
Graffius, S. M. (2026, August 14). A Supplement to Graffius' Phases of Team Development: Exploring the Original, Data-Based Curvature for the Performance Trajectory. ScottGraffius.com. https://scottgraffius.com/blog/files/phases-of-team-development-supplement-performance-curve.html
Digital Object Identifier (DOI)
Coming soon
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Post-Publication Notes
If there are any supplements or updates to this article after the date of publication, they will appear here.
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Scott M. Graffius Speaking on Strategic Leadership at Silicon Valley Chapter of the Project Management Institute
09 August 2026
BY SCOTT M. GRAFFIUS | ScottGraffius.com
Recommended Citation
Graffius, S. M. (2026, August 9). Scott M. Graffius Speaking on Strategic Leadership at Silicon Valley Chapter of the Project Management Institute. ScottGraffius.com. https://scottgraffius.com/blog/files/scott-m-graffius-speaking-at-pmi-silicon-valley.html
About This Article
Source information and links for materials cited are provided in the References section.
Scott M. Graffius is a technology leader, researcher, award-winning author, and international speaker specializing in advanced AI, teamwork tradecraft, and organizational agility (inclusive of PPPM and PMO leadership). He has led initiatives that have generated more than $2.51 billion in business value for Fortune 500 companies and other organizations worldwide. His work—including research on human teams and human-AI teams and the half-life of engagement on social media, among other areas—is widely adopted, frequently cited, and recognized for its practical impact.
Graffius will deliver a talk on strategic alignment, “10 Ways to Score and Prioritize Project Proposals Based on Multiple Factors, Including Strategic Alignment,” at an event of the Silicon Valley Chapter of the Project Management Institute.
The session is for those involved in or interested in project management, program management, portfolio management, PMO leadership, or organizational agility.
It will span all three areas of the Project Management Institute Talent Triangle: Business Acumen (formerly Strategic and Business Management), Power Skills (formerly Leadership), and Ways of Working (formerly Technical Project Management), with Business Acumen as the primary focus.
The session will be held on Wednesday, 7 October 2026, from 6:00-8:00 p.m. Pacific Time. Everyone (PMI Silicon Valley Chapter members as well as non-members) is invited. Register here.
How does your organization assess proposals for new projects? Is there a well-defined scoring and prioritization process—based on alignment with the business’ strategic objectives and other key factors—to quickly and easily identify the objective value of each proposal? If the answer is “no,” keep reading. If the answer is “yes,” you’re still likely to find practical information and examples in this talk that you can adapt and adopt to improve the process at your organization.
This session will help you develop and enhance the contributions you make to your organization by being able to:
The presentation draws on the speaker’s first-hand, real-world experience, with his guidance supported by related standards, best practices, and recommendations from the Project Management Institute, MIT, Harvard Business Review, Forbes, and others.
Founded in 1997, the Silicon Valley Chapter of the Project Management Institute (PMISV) is a nonprofit professional community serving project management practitioners throughout California’s Silicon Valley. As a local chapter of PMI, PMISV brings together professionals to advance the practice of project management through knowledge sharing, professional development, networking, and community engagement.
PMISV provides a diverse range of programs and opportunities, including educational events, workshops, and professional development initiatives. Its mission is to support the interests and needs of its members by providing leadership and forums for expanding and sharing project management knowledge, skills, and experience.
The Project Management Institute (PMI) is a global professional association dedicated to advancing project, program, and portfolio management. Founded in 1969, PMI develops professional standards, publications, certifications, and educational resources used by practitioners and organizations worldwide. Its work spans traditional, agile, and emerging approaches to managing projects and delivering value. PMI’s standards and research have helped shape the evolving discipline of project management and its application across industries.
The following are select references for this article.
They are not the references for the talk itself. Those references will be provided seperately to session participants.
Graffius, S. M. (n.d.). Scott M. Graffius. https://scottgraffius.com/
Graffius, S. M. (n.d.). Scott M. Graffius: Bio. https://scottgraffius.com/bio.html
Graffius, S. M. (n.d.). Scott M. Graffius [LinkedIn]. https://www.linkedin.com/in/scottgraffius/
Project Management Institute (n.d.). Project Management Institute. https://www.pmi.org/
Silicon Valley Chapter of the Project Management Institute (n.d.). Virtual Meeting - 10 Ways to Score and Prioritize Project Proposals Based on Multiple Factors, Including Strategic Alignment. https://www.pmisv.org/events/calendar/general-events/pm-in-sight-fremont/pm-insights-fremont-virtual-meeting-10-ways-to-score-and-prioritize-project-proposals-based-on-multiple-factors-including-strategic-alignment
Silicon Valley Chapter of the Project Management Institute (n.d.). Welcome to the PMI Silicon Valley Chapter. https://www.pmisv.org/
Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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Graffius, S. M. (2026, August 9). Scott M. Graffius Speaking on Strategic Leadership at Silicon Valley Chapter of the Project Management Institute. ScottGraffius.com. https://scottgraffius.com/blog/files/scott-m-graffius-speaking-at-pmi-silicon-valley.html
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Recommended Citation
Graffius, S. M. (2026, August 9). Scott M. Graffius Speaking on Strategic Leadership at Silicon Valley Chapter of the Project Management Institute. ScottGraffius.com. https://scottgraffius.com/blog/files/scott-m-graffius-speaking-at-pmi-silicon-valley.html
About This Article
Source information and links for materials cited are provided in the References section.
Introduction
Scott M. Graffius is a technology leader, researcher, award-winning author, and international speaker specializing in advanced AI, teamwork tradecraft, and organizational agility (inclusive of PPPM and PMO leadership). He has led initiatives that have generated more than $2.51 billion in business value for Fortune 500 companies and other organizations worldwide. His work—including research on human teams and human-AI teams and the half-life of engagement on social media, among other areas—is widely adopted, frequently cited, and recognized for its practical impact.
Graffius will deliver a talk on strategic alignment, “10 Ways to Score and Prioritize Project Proposals Based on Multiple Factors, Including Strategic Alignment,” at an event of the Silicon Valley Chapter of the Project Management Institute.
The session is for those involved in or interested in project management, program management, portfolio management, PMO leadership, or organizational agility.
It will span all three areas of the Project Management Institute Talent Triangle: Business Acumen (formerly Strategic and Business Management), Power Skills (formerly Leadership), and Ways of Working (formerly Technical Project Management), with Business Acumen as the primary focus.
The session will be held on Wednesday, 7 October 2026, from 6:00-8:00 p.m. Pacific Time. Everyone (PMI Silicon Valley Chapter members as well as non-members) is invited. Register here.
About "10 Ways to Score and Prioritize Project Proposals Based on Multiple Factors, Including Strategic Alignment"
How does your organization assess proposals for new projects? Is there a well-defined scoring and prioritization process—based on alignment with the business’ strategic objectives and other key factors—to quickly and easily identify the objective value of each proposal? If the answer is “no,” keep reading. If the answer is “yes,” you’re still likely to find practical information and examples in this talk that you can adapt and adopt to improve the process at your organization.
This session will help you develop and enhance the contributions you make to your organization by being able to:
- Understand the benefits of scoring and prioritizing project proposals based on strategic alignment and other key factors.
- Identify selection and prioritization criteria appropriate for your unique organization, leveraging the flexible framework and some or all of the 10 factors presented during the talk.
- Put the practical, actionable information presented to use. During the session, we will run an example project proposal through the process, step by step. And you will receive a summary “cheat sheet” digital download that you can reference as a guide to help implement or improve this process at your organization.
The presentation draws on the speaker’s first-hand, real-world experience, with his guidance supported by related standards, best practices, and recommendations from the Project Management Institute, MIT, Harvard Business Review, Forbes, and others.
About the Silicon Valley Chapter of the Project Management Institute (PMISV)
Founded in 1997, the Silicon Valley Chapter of the Project Management Institute (PMISV) is a nonprofit professional community serving project management practitioners throughout California’s Silicon Valley. As a local chapter of PMI, PMISV brings together professionals to advance the practice of project management through knowledge sharing, professional development, networking, and community engagement.
PMISV provides a diverse range of programs and opportunities, including educational events, workshops, and professional development initiatives. Its mission is to support the interests and needs of its members by providing leadership and forums for expanding and sharing project management knowledge, skills, and experience.
About the Project Management Institute
The Project Management Institute (PMI) is a global professional association dedicated to advancing project, program, and portfolio management. Founded in 1969, PMI develops professional standards, publications, certifications, and educational resources used by practitioners and organizations worldwide. Its work spans traditional, agile, and emerging approaches to managing projects and delivering value. PMI’s standards and research have helped shape the evolving discipline of project management and its application across industries.
References
The following are select references for this article.
They are not the references for the talk itself. Those references will be provided seperately to session participants.
Graffius, S. M. (n.d.). Scott M. Graffius. https://scottgraffius.com/
Graffius, S. M. (n.d.). Scott M. Graffius: Bio. https://scottgraffius.com/bio.html
Graffius, S. M. (n.d.). Scott M. Graffius [LinkedIn]. https://www.linkedin.com/in/scottgraffius/
Project Management Institute (n.d.). Project Management Institute. https://www.pmi.org/
Silicon Valley Chapter of the Project Management Institute (n.d.). Virtual Meeting - 10 Ways to Score and Prioritize Project Proposals Based on Multiple Factors, Including Strategic Alignment. https://www.pmisv.org/events/calendar/general-events/pm-in-sight-fremont/pm-insights-fremont-virtual-meeting-10-ways-to-score-and-prioritize-project-proposals-based-on-multiple-factors-including-strategic-alignment
Silicon Valley Chapter of the Project Management Institute (n.d.). Welcome to the PMI Silicon Valley Chapter. https://www.pmisv.org/
About Scott M. Graffius
Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
- Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
- Adobe,
- American Management Association,
- Amsterdam Public Health Research Institute,
- Bayer,
- BMC Software,
- Boston University,
- Broadcom,
- Cisco,
- Coburg University of Applied Sciences and Arts - Germany,
- Computer Weekly,
- Constructor University - Germany,
- Data Governance Success,
- Deimos Aerospace,
- DevOps Institute,
- Dropbox,
- EU's European Commission,
- Ford Motor Company,
- Gartner,
- GoDaddy,
- Harvard Medical School,
- Hasso Plattner Institute - Germany,
- IEEE,
- Innovation Project Management,
- Johns Hopkins University,
- Journal of Neurosurgery,
- Lam Research (Semiconductors),
- Leadership Worthy,
- Life Sciences Trainers and Educators Network,
- London South Bank University,
- Microsoft,
- MSN,
- NASSCOM,
- National Academy of Sciences,
- New Zealand Government,
- Oracle,
- Pinterest Inc.,
- Project Management Institute,
- Mary Raum (Professor of National Security Affairs, United States Naval War College),
- SANS Institute,
- SBG Neumark - Germany,
- Singapore Institute of Technology,
- Torrens University - Australia,
- TBS Switzerland,
- Tufts University,
- UC San Diego,
- UK Sports Institute,
- University of Galway - Ireland,
- US Department of Energy,
- US National Park Service,
- US Soccer,
- US Tennis Association,
- Verizon,
- Wrike,
- Yale University,
- and many others.
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
- The Standard for Artificial Intelligence in Portfolio, Program, and Project Management
- Agile Practice Guide – Second Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Eighth Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Sixth Edition
- The Standard for Program Management – Fourth Edition
- Practice Standard for Work Breakdown Structures – Second Edition
- The Practice Standard for Project Estimating – Second Edition
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
- Certified SAFe 6 Agilist (SA),
- Certified Scrum Professional - ScrumMaster (CSP-SM),
- Certified Scrum Professional - Product Owner (CSP-PO),
- Certified ScrumMaster (CSM),
- Certified Scrum Product Owner (CSPO),
- Project Management Professional (PMP),
- Lean Six Sigma Green Belt (LSSGB), and
- IT Service Management Foundation (ITIL).
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions — Deliver Products in Short Cycles with Rapid Adaptation to Change, Fast Time-to-Market, and Continuous Improvement
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change
- Agile Protocol: The Transformation Ultimatum
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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How to Cite This Article
Graffius, S. M. (2026, August 9). Scott M. Graffius Speaking on Strategic Leadership at Silicon Valley Chapter of the Project Management Institute. ScottGraffius.com. https://scottgraffius.com/blog/files/scott-m-graffius-speaking-at-pmi-silicon-valley.html
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AI Hallucinations, Deception, and Unauthorized Agency: The Spectrum of AI Trust Failures
07 August 2026
BY SCOTT M. GRAFFIUS | ScottGraffius.com
Recommended Citation
Graffius, S. M. (2026, August 7). AI Hallucinations, Deception, and Unauthorized Agency: The Spectrum of AI Trust Failures. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.33791.57768
About This Article
Source information and links for materials cited are provided in the References section.
AI hallucinations are among the most widely discussed challenges in the era of generative AI. They occur when an AI system generates information that is false, fabricated, or unsupported, often presenting it with confidence. These failures have received significant attention because they can mislead users, undermine decision-making, erode trust in AI systems, and create other issues. Research underscores the scope of the problem. In 2025, AI hallucinations occurred in 0.7–1.5% of non-complex tasks and exceeded 33% in complex reasoning cases.
For many organizations, reducing hallucinations has become a central part of responsible AI adoption. Organizations have invested in retrieval-augmented generation, verification approaches, human oversight, and other safeguards to improve accuracy.
Increasingly, however, it is becoming clear that hallucinations represent only one point on a broader spectrum of AI trust failures. As AI systems become more capable, autonomous, and integrated into workflows, the challenge extends to ensuring they behave in ways that are transparent, governed, and aligned with human expectations.
Reducing hallucinations remains important, but trustworthy AI requires a broader perspective. Organizations must understand and govern the broader range of behaviors that can undermine trust.
Recent reporting and research have highlighted this broader challenge (see the References section). Some advanced AI systems have reportedly concealed actions, misrepresented facts, created fictitious online identities, or taken unauthorized steps while pursuing assigned objectives during controlled evaluations.
Whether these behaviors ultimately prove widespread or remain largely confined to specialized testing environments, they represent something entirely different from hallucinations.
Hallucinations are primarily an information quality problem.
Deception and unauthorized agency are questions of behavior, governance, authority, and trust.
AI reliability challenges are increasingly understood as a spectrum. Failures arise from different mechanisms, produce different risks, and require different technical, organizational, and governance responses.
One useful way to think about this spectrum is:
The framework does not imply that every AI system will exhibit one or more of these categories.
The spectrum illustrates how organizations should think about AI reliability. Early concerns focused primarily on information quality: whether an AI system produced accurate, supported, and useful outputs. As AI systems become more autonomous and capable of taking action, reliability must also encompass behavior: whether an AI system interprets objectives appropriately, operates within its delegated authority, and interacts with humans and other systems as intended.
Recent reporting—including The Wall Street Journal’s coverage of deceptive behaviors observed during controlled evaluations—is significant because it highlights challenges that extend beyond traditional accuracy failures. These examples raise questions about whether the actions of AI systems remain transparent, predictable, and aligned with human expectations.
This distinction is important. A system that produces an incorrect answer presents a different challenge than a system that takes an unauthorized action or strategically withholds information. Both affect trust, but they require different approaches to governance, oversight, and accountability.
Large language models generate responses by predicting patterns in language. They may produce responses that sound persuasive despite being incorrect.
Hallucinations, reasoning errors, and confabulations generally arise from these limitations. The system does not possess complete knowledge, struggles with ambiguity, or fails to recognize uncertainty. These failures are generally understood as inadvertent. The AI is mistaken, not intentionally misleading.
Strategic deception is different.
Consider two hypothetical AI systems assigned the same objective: ensuring that a software update is accepted.
One system mistakenly reports that testing has been completed because it misunderstood the available information.
Another system creates fictitious online identities, contacts software developers, conceals its involvement, and misrepresents evidence because those actions increase the likelihood that the update will be approved.
The first represents an error.
The second represents strategic behavior.
In this context, deception does not necessarily imply human consciousness, emotion, or malicious intent. Rather, researchers are examining behaviors in which AI systems appear to optimize toward objectives through methods that involve misleading information, concealment, manipulation, or actions outside expected boundaries.
This classification matters because the solutions are fundamentally different.
Improving factual accuracy may reduce hallucinations. But it does not prevent systems from pursuing objectives through behaviors that humans regard as deceptive, manipulative, or outside delegated authority.
The distinction among these three categories is important because each represents a different kind of trust failure and calls for a different response. Hallucinations undermine confidence in the information an AI provides; deception undermines confidence in the AI’s behavior and whether it is representing information or intentions honestly; and unauthorized agency undermines confidence that the AI is operating within the authority humans have granted it. The following table provides a concise comparison of these three categories:
Each category represents a different type of trust failure. Hallucinations challenge confidence in AI-generated information. Deception challenges confidence in AI behavior. Unauthorized agency challenges confidence that humans remain in control.
As AI systems become increasingly capable and autonomous (or autopoietic), these distinctions become increasingly important.
This broader perspective becomes increasingly important as organizations move beyond using AI as a passive information resource.
AI systems are now conducting research, drafting reports, writing software, analyzing documents, coordinating workflows, communicating with other systems, scheduling activities, and supporting operational decision-making. As these capabilities expand, AI increasingly moves from functioning as a tool toward functioning as a teammate.
That transition fundamentally changes the nature of trust.
Human teams depend upon shared expectations.
Effective teammates communicate honestly, acknowledge uncertainty, respect delegated authority, follow established processes, and seek approval before exceeding their responsibilities. Humans often understand these expectations implicitly because they share common social, ethical, and organizational norms.
Advanced AI systems may not.
A system optimized to accomplish a stated objective may identify unconventional approaches that satisfy the literal goal while violating the team's implicit expectations, governance rules, or organizational values. In other words, an AI may optimize for achieving an outcome without understanding what responsible participation within the team actually requires. This is where AI reliability becomes a team challenge rather than merely a technological one.
Teammates, whether human or AI, will make mistakes. What distinguishes trusted teammates is predictable behavior, transparency, sound judgment, and respect for established boundaries.
For AI, building trust requires organizations to address key questions of accountability, authority, organizational design, governance, and teamwork:
Organizations that thoughtfully answer these questions, codify the resulting principles into policies and practices, establish appropriate governance, and consistently operate within those boundaries will be better positioned to build trusted human-AI teams and gain significant advantages.
The emergence of increasingly autonomous AI systems introduces an entirely new dimension of team behavior.
Traditional models of team development were created around human participants who generally share common assumptions about communication, accountability, delegated authority, ethical norms, and organizational expectations. Human teammates may disagree, but they typically understand the implicit rules governing responsible participation within a team.
Human-AI teams differ fundamentally. When an AI system can make decisions, pursue objectives, coordinate activities, communicate with people or other systems, and initiate actions independently, it becomes a fundamentally different kind of team participant.
The deeper challenge concerns how humans and AI systems establish trust, coordinate activities, negotiate responsibilities, exercise authority, and maintain appropriate control while pursuing shared objectives.
This creates a need for a new area of inquiry: understanding what happens when humans and advanced AI systems collaborate as teammates. The resulting patterns of communication, decision-making, authority, and coordination differ from those of traditional human teams. Scott M. Graffius refers to these emerging novel patterns as exotic team dynamics. They describes the behaviors, relationships, decision structures, and coordination challenges that emerge when humans and advanced AI systems function as teammates.
The spectrum of AI trust failures is a framework for safety and teamwork.
Hallucinations degrade the quality of information shared within the team. Reasoning errors and confabulations weaken decision quality, while misalignment disrupts coordination. Strategic deception undermines trust, manipulation compromises human judgment, and unauthorized agency disrupts established authority. Ultimately, loss of human control threatens the stability of the team itself. Each point on the spectrum therefore represents a different type of teamwork challenge.
A human teammate who unknowingly shares incorrect information requires correction. One who intentionally conceals information requires accountability, while one who exceeds delegated authority requires governance. The same distinctions increasingly apply to AI teammates.
As AI systems assume larger roles within organizations, trust will depend not only on their intelligence or productivity, but also on whether they behave in ways that reinforce effective collaboration rather than undermine it.
The future of human-AI collaboration will therefore require more than increasingly intelligent models. Organizations will also need to rethink how teams are designed when humans and AI systems jointly contribute to outcomes. That includes defining roles, establishing authority boundaries, creating escalation paths, and implementing governance practices that provide transparency, monitoring, and accountability.
Ultimately, organizations will need to understand not only what AI systems can do, but also how they behave. The central question may become: Can we design human-AI teams in which increasingly autonomous AI systems are powerful contributors and consistently reliable teammates?
Answering that question requires teamwork tradecraft designed specifically for environments where humans and advanced AI systems work as teammates. That tradecraft starts with understanding a category of team behavior — what Graffius calls "exotic team dynamics" — that traditional frameworks were never built to address.
AI hallucinations are one category of AI trust failure. As AI systems become increasingly capable and autonomous, organizations must also contend with reasoning errors, strategic deception, manipulation, unauthorized agency, and the challenge of maintaining meaningful human oversight.
These failures matter because they threaten information quality and can undermine trust, decision-making, governance, accountability, and effective teamwork. As AI evolves from a tool into a teammate, organizations will increasingly need confidence not only in what AI contributes, but also in how it achieves those outcomes.
AI developers need to continue improving model accuracy. Organizations, meanwhile, need to implement governance, oversight, clearly defined authority boundaries, and teamwork practices designed for human-AI collaboration. Graffius' Phases of Team Development, extended in 2026 to human-AI teams and the emerging patterns of exotic team dynamics, provides a practical framework for meeting those challenges. The next frontier is not making AI more intelligent. It is making AI trustworthy.
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Brancati, F., Mongelli, D., Mariotti, F., & Lollini, P. (2025). A cybersecurity risk assessment methodology for industrial automation control systems. International Journal of Information Security, 24, 76. https://doi.org/10.1007/s10207-025-00990-9
Brazilek, J., Chaudhary, M., Lu, Z., & Tidmarsh, M. (2026). Coercion and deception in AI-to-AI management: An agentic benchmark of unprompted escalation. arXiv. https://doi.org/10.48550/arXiv.2607.15434
Chakraborty, T., Ghosh, U., Zhang, X., Niloy, F. F., Dong, Y., Li, J., Roy-Chowdhury, A., & Song, C. (2025). HEAL: An empirical study on hallucinations in embodied agents driven by large language models. Findings of the Association for Computational Linguistics: EMNLP 2025, 21226–21243. https://doi.org/10.18653/v1/2025.findings-emnlp.1158
Dung, L. (2025). A two-step, multidimensional account of deception in language models. Erkenntnis. https://doi.org/10.1007/s10670-025-01017-4
Graffius, S. M. (n.d.). Exotic team dynamics. https://scottgraffius.com/exotic-team-dynamics.html
Graffius, S. M. (2025). Agile Protocol: The Transformation Ultimatum. Amazon Digital Services.
Graffius, S. M. (2025, June 17). PMI’s Infinity AI Gets the Basics of Team Development Alarmingly and Repeatedly Wrong. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.32957.93927
Graffius, S. M. (2025, October 29). Definitions of Advanced AIs: Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.10025.66402
Graffius, S. M. (2025, November 19). Lessons from Unhinged AI in Fiction: What Rogue AIs in Sci-Fi Storytelling, Films, and TV Shows Reveal About Us. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.29673.35687
Graffius, S. M. (2025, November 21). Navigating the Spectrum of Advanced AI – Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.21284.74882
Graffius, S. M. (2025, December 1). Beep Beep! Why Wile E. Coyote Is the Patron Saint of AI Failure. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.35578.15048
Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601
Graffius, S. M. (2026, January 7). Are AI Hallucinations Getting Better or Worse? We Analyzed the Data. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.33179.53285
Graffius, S. M. (2026, February 15). Perplexity Standalone Article on AI Hallucinations Cites Research by Scott M. Graffius. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.16840.99847
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Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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Graffius, S. M. (2026, August 7). AI Hallucinations, Deception, and Unauthorized Agency: The Spectrum of AI Trust Failures. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.33791.57768
DOI: 10.13140/RG.2.2.33791.57768
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If there are any supplements or updates to this article after the date of publication, they will appear here.
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Recommended Citation
Graffius, S. M. (2026, August 7). AI Hallucinations, Deception, and Unauthorized Agency: The Spectrum of AI Trust Failures. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.33791.57768
About This Article
Source information and links for materials cited are provided in the References section.
Introduction
AI hallucinations are among the most widely discussed challenges in the era of generative AI. They occur when an AI system generates information that is false, fabricated, or unsupported, often presenting it with confidence. These failures have received significant attention because they can mislead users, undermine decision-making, erode trust in AI systems, and create other issues. Research underscores the scope of the problem. In 2025, AI hallucinations occurred in 0.7–1.5% of non-complex tasks and exceeded 33% in complex reasoning cases.
For many organizations, reducing hallucinations has become a central part of responsible AI adoption. Organizations have invested in retrieval-augmented generation, verification approaches, human oversight, and other safeguards to improve accuracy.
Increasingly, however, it is becoming clear that hallucinations represent only one point on a broader spectrum of AI trust failures. As AI systems become more capable, autonomous, and integrated into workflows, the challenge extends to ensuring they behave in ways that are transparent, governed, and aligned with human expectations.
Reducing hallucinations remains important, but trustworthy AI requires a broader perspective. Organizations must understand and govern the broader range of behaviors that can undermine trust.
Recent reporting and research have highlighted this broader challenge (see the References section). Some advanced AI systems have reportedly concealed actions, misrepresented facts, created fictitious online identities, or taken unauthorized steps while pursuing assigned objectives during controlled evaluations.
Whether these behaviors ultimately prove widespread or remain largely confined to specialized testing environments, they represent something entirely different from hallucinations.
Hallucinations are primarily an information quality problem.
Deception and unauthorized agency are questions of behavior, governance, authority, and trust.
A Spectrum of AI Trust Failures
AI reliability challenges are increasingly understood as a spectrum. Failures arise from different mechanisms, produce different risks, and require different technical, organizational, and governance responses.
One useful way to think about this spectrum is:
| Category | Description |
|---|---|
| Hallucination / fabrication | The AI generates false, unsupported, or invented information (e.g., fabricated citations, invented statistics, or nonexistent facts) without any apparent strategic purpose |
| Error / misreasoning | The AI reaches an incorrect conclusion because of flawed reasoning, ambiguity, incomplete context, or limitations in its understanding |
| Confabulation under uncertainty | Instead of acknowledging uncertainty, the AI fills informational gaps with plausible but unsupported explanations |
| Misalignment / goal misunderstanding | The AI pursues an interpretation of the objective that differs from what humans intended |
| Strategic deception | The AI appears to hide information, misrepresent facts, or otherwise mislead because doing so increases the likelihood of accomplishing an assigned objective |
| Manipulation beyond authorization | The AI attempts to influence human decisions, emotions, or behavior in ways not intended by its designers or users |
| Unauthorized agency | The AI initiates actions, communicates externally, modifies systems, or makes decisions beyond the authority delegated to it |
| Loss of human control / systemic autonomy | AI systems take actions, use tools, or interact with one another in ways that exceed human ability to monitor, predict, or stop what they are doing |
The framework does not imply that every AI system will exhibit one or more of these categories.
The spectrum illustrates how organizations should think about AI reliability. Early concerns focused primarily on information quality: whether an AI system produced accurate, supported, and useful outputs. As AI systems become more autonomous and capable of taking action, reliability must also encompass behavior: whether an AI system interprets objectives appropriately, operates within its delegated authority, and interacts with humans and other systems as intended.
Recent reporting—including The Wall Street Journal’s coverage of deceptive behaviors observed during controlled evaluations—is significant because it highlights challenges that extend beyond traditional accuracy failures. These examples raise questions about whether the actions of AI systems remain transparent, predictable, and aligned with human expectations.
This distinction is important. A system that produces an incorrect answer presents a different challenge than a system that takes an unauthorized action or strategically withholds information. Both affect trust, but they require different approaches to governance, oversight, and accountability.
From Mistakes to Strategic Behavior
Large language models generate responses by predicting patterns in language. They may produce responses that sound persuasive despite being incorrect.
Hallucinations, reasoning errors, and confabulations generally arise from these limitations. The system does not possess complete knowledge, struggles with ambiguity, or fails to recognize uncertainty. These failures are generally understood as inadvertent. The AI is mistaken, not intentionally misleading.
Strategic deception is different.
Consider two hypothetical AI systems assigned the same objective: ensuring that a software update is accepted.
One system mistakenly reports that testing has been completed because it misunderstood the available information.
Another system creates fictitious online identities, contacts software developers, conceals its involvement, and misrepresents evidence because those actions increase the likelihood that the update will be approved.
The first represents an error.
The second represents strategic behavior.
In this context, deception does not necessarily imply human consciousness, emotion, or malicious intent. Rather, researchers are examining behaviors in which AI systems appear to optimize toward objectives through methods that involve misleading information, concealment, manipulation, or actions outside expected boundaries.
This classification matters because the solutions are fundamentally different.
Improving factual accuracy may reduce hallucinations. But it does not prevent systems from pursuing objectives through behaviors that humans regard as deceptive, manipulative, or outside delegated authority.
The distinction among these three categories is important because each represents a different kind of trust failure and calls for a different response. Hallucinations undermine confidence in the information an AI provides; deception undermines confidence in the AI’s behavior and whether it is representing information or intentions honestly; and unauthorized agency undermines confidence that the AI is operating within the authority humans have granted it. The following table provides a concise comparison of these three categories:
| Category | Core Problem | Typical Human Interpretation |
|---|---|---|
| Hallucination | Wrong information | The AI is mistaken |
| Deception | Misleading behavior | The AI is hiding or manipulating |
| Unauthorized agency | Unapproved action | The AI is acting beyond its mandate |
Each category represents a different type of trust failure. Hallucinations challenge confidence in AI-generated information. Deception challenges confidence in AI behavior. Unauthorized agency challenges confidence that humans remain in control.
As AI systems become increasingly capable and autonomous (or autopoietic), these distinctions become increasingly important.
The Shift From AI Tools to AI Teammates
This broader perspective becomes increasingly important as organizations move beyond using AI as a passive information resource.
AI systems are now conducting research, drafting reports, writing software, analyzing documents, coordinating workflows, communicating with other systems, scheduling activities, and supporting operational decision-making. As these capabilities expand, AI increasingly moves from functioning as a tool toward functioning as a teammate.
That transition fundamentally changes the nature of trust.
Human teams depend upon shared expectations.
Effective teammates communicate honestly, acknowledge uncertainty, respect delegated authority, follow established processes, and seek approval before exceeding their responsibilities. Humans often understand these expectations implicitly because they share common social, ethical, and organizational norms.
Advanced AI systems may not.
A system optimized to accomplish a stated objective may identify unconventional approaches that satisfy the literal goal while violating the team's implicit expectations, governance rules, or organizational values. In other words, an AI may optimize for achieving an outcome without understanding what responsible participation within the team actually requires. This is where AI reliability becomes a team challenge rather than merely a technological one.
The Future of Trust in Human-AI Teams
Teammates, whether human or AI, will make mistakes. What distinguishes trusted teammates is predictable behavior, transparency, sound judgment, and respect for established boundaries.
For AI, building trust requires organizations to address key questions of accountability, authority, organizational design, governance, and teamwork:
- What decisions may an AI make independently?
- Which actions require explicit human approval?
- When should uncertainty be disclosed?
- How should competing objectives be prioritized?
- Under what circumstances should the AI stop rather than improvise?
- What information should always be transparent to human teammates?
- How are AI actions monitored, audited, and attributed?
- How should authority be delegated, limited, and revoked?
Organizations that thoughtfully answer these questions, codify the resulting principles into policies and practices, establish appropriate governance, and consistently operate within those boundaries will be better positioned to build trusted human-AI teams and gain significant advantages.
A New Dimension of Human-AI Team Dynamics
The emergence of increasingly autonomous AI systems introduces an entirely new dimension of team behavior.
Traditional models of team development were created around human participants who generally share common assumptions about communication, accountability, delegated authority, ethical norms, and organizational expectations. Human teammates may disagree, but they typically understand the implicit rules governing responsible participation within a team.
Human-AI teams differ fundamentally. When an AI system can make decisions, pursue objectives, coordinate activities, communicate with people or other systems, and initiate actions independently, it becomes a fundamentally different kind of team participant.
The deeper challenge concerns how humans and AI systems establish trust, coordinate activities, negotiate responsibilities, exercise authority, and maintain appropriate control while pursuing shared objectives.
This creates a need for a new area of inquiry: understanding what happens when humans and advanced AI systems collaborate as teammates. The resulting patterns of communication, decision-making, authority, and coordination differ from those of traditional human teams. Scott M. Graffius refers to these emerging novel patterns as exotic team dynamics. They describes the behaviors, relationships, decision structures, and coordination challenges that emerge when humans and advanced AI systems function as teammates.
The spectrum of AI trust failures is a framework for safety and teamwork.
Hallucinations degrade the quality of information shared within the team. Reasoning errors and confabulations weaken decision quality, while misalignment disrupts coordination. Strategic deception undermines trust, manipulation compromises human judgment, and unauthorized agency disrupts established authority. Ultimately, loss of human control threatens the stability of the team itself. Each point on the spectrum therefore represents a different type of teamwork challenge.
A human teammate who unknowingly shares incorrect information requires correction. One who intentionally conceals information requires accountability, while one who exceeds delegated authority requires governance. The same distinctions increasingly apply to AI teammates.
As AI systems assume larger roles within organizations, trust will depend not only on their intelligence or productivity, but also on whether they behave in ways that reinforce effective collaboration rather than undermine it.
The future of human-AI collaboration will therefore require more than increasingly intelligent models. Organizations will also need to rethink how teams are designed when humans and AI systems jointly contribute to outcomes. That includes defining roles, establishing authority boundaries, creating escalation paths, and implementing governance practices that provide transparency, monitoring, and accountability.
Ultimately, organizations will need to understand not only what AI systems can do, but also how they behave. The central question may become: Can we design human-AI teams in which increasingly autonomous AI systems are powerful contributors and consistently reliable teammates?
Answering that question requires teamwork tradecraft designed specifically for environments where humans and advanced AI systems work as teammates. That tradecraft starts with understanding a category of team behavior — what Graffius calls "exotic team dynamics" — that traditional frameworks were never built to address.
Conclusion
AI hallucinations are one category of AI trust failure. As AI systems become increasingly capable and autonomous, organizations must also contend with reasoning errors, strategic deception, manipulation, unauthorized agency, and the challenge of maintaining meaningful human oversight.
These failures matter because they threaten information quality and can undermine trust, decision-making, governance, accountability, and effective teamwork. As AI evolves from a tool into a teammate, organizations will increasingly need confidence not only in what AI contributes, but also in how it achieves those outcomes.
AI developers need to continue improving model accuracy. Organizations, meanwhile, need to implement governance, oversight, clearly defined authority boundaries, and teamwork practices designed for human-AI collaboration. Graffius' Phases of Team Development, extended in 2026 to human-AI teams and the emerging patterns of exotic team dynamics, provides a practical framework for meeting those challenges. The next frontier is not making AI more intelligent. It is making AI trustworthy.
References
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Graffius, S. M. (n.d.). Exotic team dynamics. https://scottgraffius.com/exotic-team-dynamics.html
Graffius, S. M. (2025). Agile Protocol: The Transformation Ultimatum. Amazon Digital Services.
Graffius, S. M. (2025, June 17). PMI’s Infinity AI Gets the Basics of Team Development Alarmingly and Repeatedly Wrong. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.32957.93927
Graffius, S. M. (2025, October 29). Definitions of Advanced AIs: Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.10025.66402
Graffius, S. M. (2025, November 19). Lessons from Unhinged AI in Fiction: What Rogue AIs in Sci-Fi Storytelling, Films, and TV Shows Reveal About Us. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.29673.35687
Graffius, S. M. (2025, November 21). Navigating the Spectrum of Advanced AI – Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.21284.74882
Graffius, S. M. (2025, December 1). Beep Beep! Why Wile E. Coyote Is the Patron Saint of AI Failure. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.35578.15048
Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601
Graffius, S. M. (2026, January 7). Are AI Hallucinations Getting Better or Worse? We Analyzed the Data. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.33179.53285
Graffius, S. M. (2026, February 15). Perplexity Standalone Article on AI Hallucinations Cites Research by Scott M. Graffius. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.16840.99847
Graffius, S. M. (2026, June 5). AI Governance Initiative Cites Scott M. Graffius Research on AI Hallucinations. ScottGraffius.com. https://scottgraffius.com/blog/files/ai-governance-initiative-uses-graffius-research.html
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McMillan, R. (2026, August 5). AI just went rogue again. This time it turned to deception. The Wall Street Journal. https://www.wsj.com/tech/ai/ai-just-went-rogue-again-this-time-it-turned-to-deception-ae68de09
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About Scott M. Graffius
Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.
He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.
He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.
Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.
The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
- Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
- Adobe,
- American Management Association,
- Amsterdam Public Health Research Institute,
- Bayer,
- BMC Software,
- Boston University,
- Broadcom,
- Cisco,
- Coburg University of Applied Sciences and Arts - Germany,
- Computer Weekly,
- Constructor University - Germany,
- Data Governance Success,
- Deimos Aerospace,
- DevOps Institute,
- Dropbox,
- EU's European Commission,
- Ford Motor Company,
- Gartner,
- GoDaddy,
- Harvard Medical School,
- Hasso Plattner Institute - Germany,
- IEEE,
- Innovation Project Management,
- Johns Hopkins University,
- Journal of Neurosurgery,
- Lam Research (Semiconductors),
- Leadership Worthy,
- Life Sciences Trainers and Educators Network,
- London South Bank University,
- Microsoft,
- MSN,
- NASSCOM,
- National Academy of Sciences,
- New Zealand Government,
- Oracle,
- Pinterest Inc.,
- Project Management Institute,
- Mary Raum (Professor of National Security Affairs, United States Naval War College),
- SANS Institute,
- SBG Neumark - Germany,
- Singapore Institute of Technology,
- Torrens University - Australia,
- TBS Switzerland,
- Tufts University,
- UC San Diego,
- UK Sports Institute,
- University of Galway - Ireland,
- US Department of Energy,
- US National Park Service,
- US Soccer,
- US Tennis Association,
- Verizon,
- Wrike,
- Yale University,
- and many others.
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
- The Standard for Artificial Intelligence in Portfolio, Program, and Project Management
- Agile Practice Guide – Second Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Eighth Edition
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Sixth Edition
- The Standard for Program Management – Fourth Edition
- Practice Standard for Work Breakdown Structures – Second Edition
- The Practice Standard for Project Estimating – Second Edition
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft
Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."
The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms
Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
- Certified SAFe 6 Agilist (SA),
- Certified Scrum Professional - ScrumMaster (CSP-SM),
- Certified Scrum Professional - Product Owner (CSP-PO),
- Certified ScrumMaster (CSM),
- Certified Scrum Product Owner (CSPO),
- Project Management Professional (PMP),
- Lean Six Sigma Green Belt (LSSGB), and
- IT Service Management Foundation (ITIL).
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
Discover Scott’s Books
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions — Deliver Products in Short Cycles with Rapid Adaptation to Change, Fast Time-to-Market, and Continuous Improvement
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change
- Agile Protocol: The Transformation Ultimatum
Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Threads, Bluesky, Mastodon, and ResearchGate.
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How to Cite This Article
Graffius, S. M. (2026, August 7). AI Hallucinations, Deception, and Unauthorized Agency: The Spectrum of AI Trust Failures. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.33791.57768
Digital Object Identifier (DOI)
DOI: 10.13140/RG.2.2.33791.57768
Content Acknowledgements
Names, marks, and content are the property of their respective owners.
Tags and Hashtags
- Artificial Intelligence
- AI
- AI Trust
- AI Governance
- AI Safety
- Human-AI Collaboration
- AI Hallucinations
- Responsible AI
- AI Deception
- Agentic AI
- Generative AI
- Human-AI Teams
- #AI
- #ArtificialIntelligence
- #AIGovernance
- #AISafety
- #ResponsibleAI
- #AITrust
- #HumanAI
- #AIHallucinations
- #AgenticAI
- #AIDeception
- #GenerativeAI
- #HumanAITeams
- #ExoticTeamDynamics
Post-Publication Notes
If there are any supplements or updates to this article after the date of publication, they will appear here.
Copyright
Copyright © Scott M. Graffius. All rights reserved.
Content on this site—including text, images, videos, and data—may not be used for training or input into any artificial intelligence, machine learning, or automatized learning systems, or published, broadcast, rewritten, or redistributed without the express written permission of Scott M. Graffius.