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Which Performs Best: Humans, AI, or Human-AI Collaboration? We Analyzed the Data

01 October 2026
BY SCOTT M. GRAFFIUS | ScottGraffius.com



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Recommended Citation

Graffius, S. M. (2026, October 1). Which Performs Best: Humans, AI, or Human-AI Collaboration? We Analyzed the Data. ScottGraffius.com. https://scottgraffius.com/blog/files/which-performs-best-humans-ai-or-human-ai-collab.html



About This Article

Source information and links for materials cited are provided in the References section.



Introduction



Which performs best: humans, AI, or human-AI collaborations?

Prior studies have reached different conclusions about whether human-AI combinations outperform humans or AI alone. To answer this question, we conducted a deep-dive analysis of empirical evidence across a broad range of studies to determine what the data show. The findings might surprise you.

Methodology



Research question

This article examines the central question: Do human-AI collaborations outperform humans and AI working independently? A bonus question is: Under what conditions does each configuration generally perform best?

"Human-AI collaboration" is used broadly in this analysis. It includes human-AI teams, human-AI decision-making, hybrid workflows, human-AI collectives, and other arrangements in which humans and AI jointly collaborate on an outcome.

The term collaborative advantage is used more narrowly. A human-AI system demonstrates a collaborative advantage when its performance exceeds both human-only and AI-only performance on the relevant task.

Evidence base

This analysis draws on 42 unique published studies.

All 42 sources were published within the past three years (2024-2026): 4 in 2024, 18 in 2025, and 20 in 2026. This reflects the fast pace of AI development and ensures the evidence speaks to current systems.

The studies cover a range of domains, including medicine and healthcare, education, creativity, decision-making, risk assessment, human factors, teamwork, intelligence analysis, and other areas.

The studies also differ considerably in design. Some directly compare human-only, AI-only, and human-AI configurations. Others compare two configurations. Some examine human-AI collaboration more indirectly by studying factors such as trust, reliance, explanation, workflow, role allocation, or decision processes.

That heterogeneity is less of a limitation for the present objective, which is to characterize the broader empirical landscape and identify recurring patterns.

Classification of findings

Each study was reviewed and classified according to the strongest conclusion supported by its findings.

The outcome categories were:

  • Humans alone perform best
  • AI alone performs best
  • Human-AI collaboration performs best
  • Findings are inconclusive

The classifications identify the principal result relevant to the core question. Do not interpret this as meaning every study was a direct three-way comparison.

The inconclusive category was reserved for studies in which the authors reported no meaningful difference.

Each study in the table below is assigned one principal designation. The four summary rows at the bottom of the table are simple tallies of those designations: the first pair (count and percentage) covers all 42 studies, and the second pair excludes the five inconclusive studies, leaving 37.

Results

The 42-study evidence base

The following table is the central evidence map for the analysis.

#Short referenceDomainHumans Perform BestAI Performs BestHuman-AI Collaboration Performs BestInconclusive
1Vaccaro et al. (2024)Multiple domains✓
2Hemmer et al. (2025)Decision-making✓
3Liu et al. (2025)Decision-making✓
4Wang et al. (2026)Healthcare✓
5Zöller et al. (2025)Medicine/diagnosis✓
6Berretta et al. (2026)Decision-making✓
7Vo (2025)Human-AI interaction✓
8Lai & Rau (2026)Human-AI teams✓
9Memmert et al. (2026)Decision-making/teamwork✓
10Akben et al. (2026)Decision-making✓
11Fügener et al. (2025)Operations/decision-making✓
12Hua et al. (2025)Human-AI teams✓
13Flathmann et al. (2024)Human-AI teaming✓
14Schmutz et al. (2024)Human factors/teamwork✓
15Krzywdzinski et al. (2026)Organizational/teamwork✓
16Mascareño et al. (2026)Creativity/innovation✓
17Ong et al. (2026)Decision-making✓
18Mayer et al. (2026)Human-AI interaction✓
19Wang et al. (2026)Intelligence analysis✓
20Gonzalez et al. (2026)Human-AI teaming✓
21Senoner et al. (2024)Manufacturing/decision support✓
22Wu et al. (2025)Human-AI collaboration✓
23Winter (2025)Teamwork/creativity✓
24Liel & Zalmanson (2025)Decision-making✓
25Rojas et al. (2025)Human-AI teams✓
26Simpson et al. (2026)Teamwork✓
27Cristofaro & Giardino (2026)Cognition/AI use✓
28Ngo (2025)Healthcare/public sector✓
29Kuang et al. (2026)Usability/user research✓
30Li et al. (2025)Risk assessment✓
31Kang et al. (2025)Medicine/imaging✓
32Zeng et al. (2026)Cybersecurity/decipherment✓
33Al-Ali et al. (2026)Decision-making✓
34Tannoubi et al. (2026)Education✓
35Gerlich (2025)Education/cognition✓
36Luan et al. (2025)Creativity✓
37Tang et al. (2025)Creativity✓
38Jin & Rho (2025)Human-AI decision-making✓
39Choi et al. (2026)Human-AI interaction✓
40Raj et al. (2026)Creative writing✓
41Choung et al. (2026)Human-AI interaction✓
42Chen (2025)Qualitative research✓
# of 4274265
% of 4216.7%9.5%61.9%11.9%
# excl. inconclusive7426
% excl. inconclusive18.9%10.8%70.3%


Additional information appears in the Table Annotations section, before the References.

Discussion



Human-AI collaboration is the largest single category in this evidence set. Twenty-six of the 42 studies (61.9%) were classified as favoring human-AI collaboration. When the five inconclusive studies were removed, the figure is 26 out of 37 (70.3%).

However, collectively, the studies do not indicate a single best configuration:

  • Of the 42 studies, 26 (61.9%) favored human-AI collaboration, 7 (16.7%) favored humans alone, 4 (9.5%) favored AI alone, and 5 (11.9%) were inconclusive.
  • Excluding the five inconclusive studies, there are 37 studies. Of them, 26 (70.3%) favored human-AI collaboration, 7 (18.9%) favored humans alone, and 4 (10.8%) favored AI alone.

In Cases of Work Involving a Specific Task

The studies in this analysis span different levels of focus. Some examine broad forms of work, such as projects, that comprise multiple tasks, while others examine a single task.

At the task level, an organization may have one task where AI is typically the best configuration, another where humans are, and a third where the two together do best.

For each important task, it helps to ask:

  1. What does the task require?
  2. What does the human bring, and what does the AI bring?
  3. Where do those differences help, and where might they cause errors or friction?
  4. What workflow would let the strengths combine?
  5. How does each configuration actually perform: human alone, AI alone, and the two together?
  6. What does the data say?

Generally, human-AI collaboration looks most promising for conceptual and generative work where humans and AI bring different capabilities, such as ideation and brainstorming, content design and creation, and niche domain problem-solving. Human-only work may remain the better choice for tasks with high emotional complexity, unstructured environments, or ethical nuance. AI-only execution may suit analytical and evaluative work, such as high-volume data sorting, pattern recognition, and statistical forecasting.

Limitations



Buckle up: There are lots of limitations to factor and negotiate.

  • The 42 publications are not methodologically uniform. Some directly compare humans, AI, and human-AI configurations. Others compare only two conditions or examine aspects of human-AI collaboration. The percentages reported here describe this particular evidence set; they are not pooled effect estimates.
  • The studies cover different domains and tasks.
  • AI capabilities are changing rapidly. A result obtained with an earlier model does not necessarily predict the performance of a current or future model. This is why the analysis prioritizes 2024–2026 publications and should be updated as technology and the research base develop.
  • Different studies use different designs or performance measures. Accuracy, speed, quality, creativity, diagnostic performance, decision quality, and other measures are not interchangeable. A collaboration can improve one dimension while worsening another.
  • Some studies examine laboratory or controlled settings rather than long-term real-world teams. Real-world collaboration introduces factors such as organizational culture, training, incentives, trust, workload, accountability, and learning over time.
  • Publication bias is possible. Studies reporting interesting positive or negative results may be more likely to be published or noticed than studies finding little or no difference. Vaccaro et al. specifically identify possible publication bias and variation in study designs as limitations of the existing evidence base.
  • Classifications in this article necessarily involve judgment. The intent was to classify the principal finding relevant to the core question while avoiding overstatement.

Conclusion



This article is longer than Interstellar. So we’re wrapping it up.

Which performs best: humans alone, AI alone, or human-AI collaboration? The empirical evidence indicates that human-AI collaboration generally performs better than either humans or AI alone.

Our analysis of 42 studies found that human-AI collaboration was the largest single best-performing category in the evidence set. Twenty-six studies (61.9%) showed human-AI collaboration as the best-performing configuration. Excluding the five studies that were classified as inconclusive, the figure was 70.3% (compared with 18.9% for humans and 10.8% for AI). The other 16 studies favored humans alone (7), AI alone (4), or were inconclusive (5), showing mixed results.

There is no universal winner. The best configuration depends on the endeavor. Conceptual and generative work is most effectively handled by humans and AI working together. For cognitive and relational work, humans have the edge. And for analytical and evaluative work, AI does.

Yet, across the evidence of a broad range of 42 studies, human-AI collaboration emerges as the strongest overall approach. As a larger implication, an advantage belongs to human-AI teams that effectively handle what Scott M. Graffius calls "exotic team dynamics"—the novel, strange, and often counterintuitive patterns that emerge when people and AI collaborate as teammates.



Note



Scott M. Graffius' "Phases of Team Development" provides unique insights and practical strategies to help teams become more effective and successful. He developed it in 2008, and he updates it periodically. Graffius’ work is used by businesses, professional associations, government agencies, universities, and publications around the world. Select 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.

Graffius expanded the 2026 edition of his "Phases of Team Development" beyond human-only teams. He added human-AI teams, with guidance on "exotic team dynamics." “Exotic team dynamics” describe the novel and often counterintuitive patterns that emerge when humans and advanced artificial intelligence function as teammates, and provide guidance on how to succeed with them. Understanding and navigating these complexities is essential for organizations seeking to unlock the full potential of human-AI teamwork and gain a competitive advantage. Explore "Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update" and other resources detailed in the References to learn more.



Scott M. Graffius has generated over $3.1 billion in business value for Fortune 500 companies and other organizations around the world. Put that track record to work for you. For speaking engagements, use the request form; for other inquiries, email him.



Table Annotations



Notes

  1. Vaccaro et al. (2024): Overall, AI was indicated. On average, human–AI combinations performed worse than the better of human-only or AI-only. Gains were more common in creation tasks; losses in decision tasks. When humans > AI, combinations often gained; when AI > humans, combinations often lost.
  2. Hemmer et al. (2025): Overall, human-AI collaboration was indicated. Supports complementary team performance (CTP) when information or capability asymmetries exist and are properly leveraged; CTP is not automatic.
  3. Liu et al. (2025): Overall, AI was indicated. Medical AI augments clinicians, but full complementarity (HMT > both alone) is rare. Simultaneous teaming mode and junior clinicians show more benefit; sequential mode less so.
  4. Wang et al. (2026): Inconclusive was indicated. Mixed / non-significant or uncertain advantages for H+AI vs human-only on key metrics; H+AI did not universally outperform AI-only in three-arm settings; high prediction-interval uncertainty.
  5. Zöller et al. (2025): Overall, human-AI collaboration was indicated. Collectives outperformed individual physicians, physician collectives, individual LLMs, and LLM ensembles by leveraging complementary error patterns.
  6. Berretta et al. (2026): Overall, human-AI collaboration was indicated. AI-first then human workflow was best overall (faster than human-only, fewer errors than AI-only); human–AI improved certain psychological measures.
  7. Vo (2025): Inconclusive was indicated. Human outperformed on novelty; AI on style in some stages; collaboration finished last on key CPSS ratings. Results varied by design stage and criterion.
  8. Lai & Rau (2026): Inconclusive was indicated. Leadership effectiveness was comparable across human-only and AI-only; hybrid structures did not significantly outperform single-leader conditions.
  9. Memmert et al. (2026): Overall, human-AI collaboration was indicated. Individual humans did not improve with GLM support, but the human–AI dyad collectively achieved superior/complementary performance on standard brainstorming metrics.
  10. Akben et al. (2026): Overall, human-AI collaboration was indicated. Aggregated / collective human–AI intelligence outperformed either component alone.
  11. Fügener et al. (2025): Overall, human-AI collaboration was indicated. Appropriate human–AI role allocation produced higher performance than alternatives.
  12. Hua et al. (2025): Overall, human-AI collaboration was indicated. Conditional support for teaming; poor AI teammates can substantially deteriorate performance.
  13. Flathmann et al. (2024): Overall, human-AI collaboration was indicated. Training and preparation influenced human–AI team performance positively under studied conditions.
  14. Schmutz et al. (2024): Overall, humans were indicated. Human–AI teams can underperform when core mechanisms (trust, communication, coordination, shared cognition) are weak.
  15. Krzywdzinski et al. (2026): Overall, human-AI collaboration was indicated. Team organization and communication influenced AI-assisted performance positively.
  16. Mascareño et al. (2026): Overall, humans were indicated. Proximal AI collaboration hindered innovation under certain conditions.
  17. Ong et al. (2026): Overall, AI was indicated. Collaboration improved human performance under some conditions but remained below LLM performance overall.
  18. Mayer et al. (2026): Overall, human-AI collaboration was indicated. Effective collaboration is possible under appropriate AI adaptation strategies; performance–preference trade-offs exist.
  19. Wang et al. (2026): Overall, human-AI collaboration was indicated. Hybrid workflow produced the highest analyst accuracy.
  20. Gonzalez et al. (2026): Overall, human-AI collaboration was indicated. The framework identifies conditions supporting effective complementary teaming.
  21. Senoner et al. (2024): Overall, human-AI collaboration was indicated. Explainable AI improved human performance in collaboration.
  22. Wu et al. (2025): Overall, human-AI collaboration was indicated. Collaboration improved immediate task performance (motivation effects noted separately).
  23. Winter (2025): Overall, humans were indicated. Human teams outperformed human–AI teams under the study’s competitive conditions.
  24. Liel & Zalmanson (2025): Overall, humans were indicated. Participants sometimes performed better without AI recommendations.
  25. Rojas et al. (2025): Overall, human-AI collaboration was indicated. Trust dynamics affected performance in human–human–AI teams.
  26. Simpson et al. (2026): Overall, humans were indicated. Human-led teams generally outperformed AI-led teams.
  27. Cristofaro & Giardino (2026): Overall, human-AI collaboration was indicated. Conditional synergy depending on AI-use intensity and cognitive engagement.
  28. Ngo (2025): Overall, AI was indicated. AI augmentation was observed, but generally negative collaboration effects.
  29. Kuang et al. (2026): Overall, human-AI collaboration was indicated. Tailored AI + human review produced the highest-quality results.
  30. Li et al. (2025): Overall, human-AI collaboration was indicated. Human–AI approach exceeded both human-only and AI-only performance.
  31. Kang et al. (2025): Overall, human-AI collaboration was indicated. The combined approach produced the highest accuracy and fastest processing.
  32. Zeng et al. (2026): Overall, human-AI collaboration was indicated. Human–computer collaboration improved multiple decipherment measures.
  33. Al-Ali et al. (2026): Overall, human-AI collaboration was indicated. Adaptive hybrid exceeded human-only and uncalibrated AI; calibrated AI was slightly higher on raw reward in some comparisons.
  34. Tannoubi et al. (2026): Overall, human-AI collaboration was indicated. Hybrid human–AI lesson design generally produced the strongest outcomes.
  35. Gerlich (2025): Overall, human-AI collaboration was indicated. Guided human–AI interaction produced stronger critical reasoning.
  36. Luan et al. (2025): Overall, human-AI collaboration was indicated. Collaboration did not automatically improve joint creativity; guided co-creation supported better-designed collaboration.
  37. Tang et al. (2025): Overall, humans were indicated. Human–human teams performed better on divergent thinking.
  38. Jin & Rho (2025): Overall, human-AI collaboration was indicated. Explanations improved accuracy and reduced inappropriate reliance.
  39. Choi et al. (2026): Inconclusive was indicated. Primarily examined perceptions of trust and fairness rather than comparative task-performance outcomes.
  40. Raj et al. (2026): Overall, humans were indicated. Participants consistently devalued AI-generated creative writing compared with human-generated work (primarily a preference/perception finding).
  41. Choung et al. (2026): Inconclusive was indicated. Primarily examined fairness and trust perceptions.
  42. Chen (2025): Overall, human-AI collaboration was indicated. Human oversight affected efficiency and depth positively in qualitative inquiry.



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Vaccaro, M., Almaatouq, A., & Malone, T. (2024). When combinations of humans and AI are useful: A systematic review and meta-analysis. Nature Human Behaviour, 8, 2293–2303. https://doi.org/10.1038/s41562-024-02024-1

Vo, K. H. T. (2025). “Who” designs better? A competition among human, artificial intelligence and human–AI collaboration. Design Science, 11, e37. https://doi.org/10.1017/dsj.2025.10029

Wang, G., Zhang, K., Jiang, J., Wang, C., Bi, H., Liang, H., Qi, Z., Huang, Y., Li, Y., & Yang, X. (2026). Human–large language model collaboration in clinical medicine: A systematic review and meta-analysis. npj Digital Medicine, 9, Article 195. https://doi.org/10.1038/s41746-026-02382-2

Wang, L., Huang, Q., Wang, K., Lou, J., & Yuan, C. (2026). Comparison of human-AI collaboration modes in cross-platform public opinion analysis: An experimental study on analyst performance and cognitive load. International Journal of Human–Computer Interaction. Advance online publication. https://doi.org/10.1080/10447318.2026.2728615

Winter, J. (2025). AI teammates and human performance: Evidence for commitment deficits. Computers in Human Behavior Reports, 20, 100828. https://doi.org/10.1016/j.chbr.2025.100828

Wu, S., Liu, Y., Ruan, M., Chen, S., & Xie, X.-Y. (2025). Human-generative AI collaboration enhances task performance but undermines human's intrinsic motivation. Scientific Reports, 15, 15105. https://doi.org/10.1038/s41598-025-98385-2

Zeng, S., Bai, J., Shi, J., Li, Y., Zhao, Y., & Shi, Y. (2026). Human–computer collaborative approach to the decipherment of oracle bone inscriptions with generative adversarial networks. npj Heritage Science, 14, 232. https://doi.org/10.1038/s40494-026-02509-4

Zöller, N., Berger, J., Lin, I., Fu, N., Komarneni, J., Barabucci, G., Laskowski, K., Shia, V., Harack, B., Chu, E. A., Trianni, V., Kurvers, R. H. J. M., & Herzog, S. M. (2025). Human–AI collectives most accurately diagnose clinical vignettes. Proceedings of the National Academy of Sciences, 122(24), e2426153122. https://doi.org/10.1073/pnas.2426153122



About Scott M. Graffius



Scott M. Graffius is a technology leader, researcher, award-winning author, practitioner, consultant, thought leader, and international public speaker specializing in AI, Agile, project/program/portfolio management (PPPM), PMO leadership, and teamwork tradecraft. His work explores the intersection of human ingenuity and emerging technology, with a strong practitioner voice grounded in research, experimentation, and experience. His focus includes innovation, organizational performance, and the evolving practice of teamwork, including the "exotic team dynamics" that emerge when people collaborate with advanced artificial intelligence (agentic, autonomous, or autopoietic AI). Graffius has delivered more than $3.1 billion in business value for Fortune 500 companies and other organizations spanning technology, entertainment and media, financial services, healthcare, government, and other industries.

Businesses, professional associations, government agencies, universities, publications, and media outlets use Graffius and his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Innovation Project Management, 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 highlight his experience, leadership, contributions, research, and enduring influence across industries and institutions worldwide.

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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 enterprise 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 media, and more.

He has experience with consumer, business, reseller, government, and international markets.

Additional information is on LinkedIn.

Award-Winning Author

Graffius has authored three books.

Graffius' first book, Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, earned 17 awards. It provides a practical, step-by-step guide to Scrum, enabling teams to deliver products in short cycles with rapid adaptation, fast time-to-market, and continuous improvement—which supports innovation and drives competitive advantage.

  • Paperback ISBN-13: 9781533370242
  • Kindle ASIN: B01FZ0JIIY

Additional information on Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions is here.

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His second book, 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, was named one of the best Scrum books of all time by BookAuthority. It tells the compelling story of an entertainment company's agile transformation—offering lessons that apply across industries.

  • Paperback ISBN-13: 9781072447962
  • Kindle ASIN: B07R9LJLPJ

Additional information on 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 is here.

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Agile Protocol: The Transformation Ultimatum, is his third book—and his first work of fiction.

It's a fast-paced satirical story by that dismantles corporate Agile cosplay and other forms of "fake Agile" while delivering practical insights, actionable guidance, and proven practices for real-world Agile transformation success.

Packed with humor, quirky characters, sharp commentary on corporate culture and workplace absurdities, and actionable tips, it’s a must-read for Scrum Masters, Product Owners, Agile Coaches, Agile Project Managers, and other professionals interested in Agile project management and enterprise agility.

  • Kindle ASIN: B0F2SJ83WT
  • Audible ASIN: B0DJG163R5

Additional information on Agile Protocol: The Transformation Ultimatum is here.

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International Public Speaker

Organizations worldwide engage Graffius to present on technology (including AI), Agile, project management, program management, portfolio management, and enterprise PMO leadership. He crafts and delivers unique and compelling talks and workshops.

Graffius has conducted 99 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), Future of Work and Advanced AI (Paris, France), and more.

With an average rating of 4.82 (on a scale of 1-5), sessions are highly valued.

The 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,
  • BCG,
  • BMC Software,
  • Boston Consulting Group (BCG),
  • 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 Marketing,
  • 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,
  • Ohio State University,
  • Oracle,
  • Pinterest Inc.,
  • Project Management Institute,
  • Mary Raum (Professor of National Security Affairs, United States Naval War College),
  • Round Square Global Educational Network,
  • Royal Australasian College of Physicians (RACP),
  • 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.

Authority on Teamwork Tradecraft

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Graffius is a renowned and highly-cited 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.

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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 is here.

Expert on Temporal Dynamics on Social Media Platforms

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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, 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/program/portfolio management (PPPM), and PMO leadership. Businesses and other organizations leverage Graffius’ insights to drive their success.



Booking


Graffius has generated over $3.1 billion in business value for Fortune 500 companies and other organizations served. Put that track record to work for you. For speaking engagements, use the request form; for other inquiries, email him.



Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Bluesky, Mastodon, and ResearchGate.



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List of Additional Articles



Read more.

Meta CTO Called the AI Reorganization “Atrocious” — What Went Wrong and the Lessons for Human-AI Teams

A Critical Analysis of "AI and Quantum Computers Will Be Frenemies"

A Supplement to Graffius' Phases of Team Development: Exploring the Original, Data-Based Curvature for the Performance Trajectory

Scott M. Graffius Speaking on Strategic Leadership at Silicon Valley Chapter of the Project Management Institute

AI Hallucinations, Deception, and Unauthorized Agency: The Spectrum of AI Trust Failures

A Critical Analysis of "The Social Cost of an AI Teammate: How an Artificial Teammate Reshapes Human-Human Communication in Small-Team Decision-Making"

Journal of Marketing Cites Scott M. Graffius' Research on the Half-Life of Social Media

The Evolution of Pair Programming and the Rise of Exotic Team Dynamics

Number 1 University in England for Student Satisfaction Features Scott M. Graffius' "Phases of Team Development"

Royal Australasian College of Physicians Licenses Scott M. Graffius' "Phases of Team Development" Intellectual Property on Teamwork Tradecraft

Exotic Team Dynamics: How Advanced AI Teammates Are Unlocking New Levels of Innovation, Performance, and Success

A Critical Analysis of "Platform-Specific Data Decay Patterns: A Comparative Study of Twitter, Reddit, and TikTok" and Its Reference to Research by Scott M. Graffius

Round Square Global Educational Network Features Scott M. Graffius’ Phases of Team Development

Meta's Muse Missed the Mark: Hollywood’s Win Against Big Tech on AI Consent and Likeness Rights

Scott M. Graffius Contributed to Seven Project Management Institute (PMI) Standards
Quantum Computing, Advanced AI Acceleration, and the Rise of Exotic Team Dynamics in Human-AI Teams

Ohio State University Course Features Scott M. Graffius' "Phases of Team Development"

Questions About Integrity at UNC Chapel Hill

Scrum Isn’t Just for Coding

Book on Generative and Agentic AI Cites Scott M. Graffius' Work on AI

IPA / ADAL Publication Plagiarized Another’s Copyrighted Work and Violated Intellectual Property Rights

UC Davis' Integrity Is Circling the Drain

L'avenir du Travail et de l'IA Avancée / Future of Work and Advanced AI

NCCI / UNC Chapel Hill Publication Features Scott M. Graffius' Work

Boston Consulting Group (BCG) Features Scott M. Graffius' Research on Social Media Content Half-Life

UC Davis Used Scott M. Graffius' "Phases of Team Development" Intellectual Property

Medical, Pharma, and Healthcare Organizations Are Using Scott M. Graffius' "Phases of Team Development"

Government of Ireland Report Features Research by Scott M. Graffius

Scott M. Graffius Contributed to The Standard for Artificial Intelligence in Portfolio, Program, and Project Management

AI Governance Initiative Cites Scott M. Graffius Research on AI Hallucinations

Scott M. Graffius Contributed to the Agile Practice Guide - Second Edition

Scott M. Graffius Generated Over $2.51 Billion in Business Value for Fortune 500 Companies and Other Organizations

Government of Canada Features Research by Scott M. Graffius

"Strategic Business Research" Journal Cites Work of Scott M. Graffius

IEEE Access Publication Features Scott M. Graffius’ Research on the Half-Life of Social Media

The Agile Coach: 2026 Edition

Scott M. Graffius’ Work Cited in International Peer-Reviewed Journal on Digital Transformation

Phases of Team Development in Elite Sport

A Critical Analysis of COVID-19 Treatment Search Trends and Media Coverage Study Citing Scott M. Graffius' Work

Human-AI Teamwork: Master the Exotic Team Dynamics That Emerge When Collaborating with Advanced AI -- Or Be Outplayed

"Agile Scrum" by Scott M. Graffius Now Featured on Grokipedia

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Thinkers360 Honors Scott M. Graffius as a 2026 Top Agile Thought Leader

Agile's Journey Through the Decades: Update for 2026

BMC Software Features Content from Scott M. Graffius' Book

Peer-Reviewed Journal Cited Work of Scott M. Graffius
University of Waterloo Features Graffius' "Phases of Team Development" in Course Materials

Perplexity Standalone Article on AI Hallucinations Cites Research by Scott M. Graffius

Handling the Saboteur Within: Lessons from a 3-Letter Agency on Spotting and Stopping Intentional and Unintentional Sabotage

A Deep Dive Into the Typical Engagement Pattern for Social Media Posts

Most Valuable IT Certifications: Update for 2026

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University of Greenwich Features Graffius' Phases of Team Development


10 Essential Agile Books: Curated Recommendations for Agile Professionals

Lifespan (Half-Life) of Social Media Posts: Update for 2026

Scott M. Graffius' Research on the Half-Life of Social Media was Cited in a Peer-Reviewed Study Published in Telecommunications Policy, a Leading Academic Journal

Are AI Hallucinations Getting Better or Worse? We Analyzed the Data

Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update

Lessons from Yesterday’s Tomorrowland

Scott M. Graffius’ Update to His "Phases of Team Development” Coming Early 2026

A Data-Driven Analysis of the Evolution of Project Management: Tasks, Trends, and AI

Actionable Insights. Global Impact. Scott M. Graffius.

Beep Beep! Why Wile E. Coyote Is the Patron Saint of AI Failure

Social Media Half-Life Research Cited in Prestigious Peer-Reviewed Medical Journal

Navigating the Spectrum of Advanced AI – Agentic, Autonomous, and Autopoietic

Lessons from Unhinged AI in Fiction: What Rogue AIs in Sci-Fi Storytelling, Films, and TV Shows Reveal About Us

Scott M. Graffius Contributed to and Reviewed the PMBOK Guide, 8th Edition — the Global Standard for Project Management

UK Sports Institute Features Teamwork and Leadership Work of Scott M. Graffius

Definitions of Advanced AIs: Agentic, Autonomous, and Autopoietic

HAN University of Applied Sciences Features the Work of Scott M. Graffius

Gifts That Inspire Joy

Evergreen Echoes: How Pinterest Inc. and Pinterest Japan Spotlighted Scott M. Graffius’ Research on the Half-Life of Social Media Content

Scott M. Graffius’ Team Development Work Lights Up the University of Tasmania’s Curriculum

Taiwan’s Leading Outlet for Technology and Innovation Spotlights Graffius’ Research on Social Media Temporal Dynamics

Scott M. Graffius’ Insights on AI, Agile, Gaming, XR, and Defense Transformation Cited by MSN in Their Coverage of Innovation and Leadership in the Sector

Top Predictions of 2024, Tested in 2025

Government of Finland Agency Features Graffius' Phases of Team Development IP

Scott M. Graffius Premieres His New "Exotic Team Dynamics: Human-AI Collaboration" Talk at Corporate Event in Las Vegas

Environmental Science Journal References Scott M. Graffius’ Project Management Work

AI Institute of Switzerland Features Scott M. Graffius’ Work on Algorithms

Exotic Team Dynamics: The New Frontier of Human–AI Collaboration

Scott M. Graffius’ Work Featured at ACM DIS ’25

Climbing the Ladder: The Head of Agile/PMO’s Organizational Proximity to the CEO is Closer Than Ever

Harness Sci-Fi and Speculative Design While Embracing Imperfection to Drive Innovation and Proactively Predict and Prepare for the Future

Scott M. Graffius’ “Agile Scrum” Book Featured in a Publication of the Associação Nacional de Educação Católica do Brasil (ANEC)

Setting Direction with OKRs and Tracking Progress with KPIs: A Guide for Agile, Project Management, and Tech Teams

AI Showcase Showdown: Ranking AI Accuracy on Project Management Basics

BookAuthority Features “Agile Scrum” by Scott M. Graffius in “10 Agile Software Development Books That Define the Field”

Exploring Team Dynamics, Adaptability, and Creative Problem-Solving Through Felix the Cat’s Metaphorical Toolkit

Mind Games and Master Plans: How PsyOps Exploit Psychological Phenomena

The “Pants-on-Fire Index for AI”

16 Causes of Technical Debt and How to Avoid It

PMI’s Infinity AI Gets the Basics of Team Development Alarmingly and Repeatedly Wrong

Agile for Unicorns: 7 Keys to Thrive; Scott M. Graffius’ Workshop

Scott M. Graffius’ “Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions” Featured in Prestigious National Academies of Sciences Publication

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"Agile Protocol" and the Power of Satire, Parody, and Humor

AI in Agile: Benefits, Risks, Outlook

Hostinger Highlights Scott M. Graffius’ “Agile Protocol” Book in Feature on Software Projects

French Ministry of Culture Links to Scott M. Graffius Research in Their Guide for Responsible Digital Communication

National Science Foundation’s LTER Network Features Scott M. Graffius’ Phases of Team Development IP

Waterfall vs. Agile: What’s Fixed, What’s Flexible, and Why It Matters

Scott M. Graffius Delivering $2.3 Billion in Value Through AI, Agile, and Project/PMO Leadership

The Problem with Heroes in Agile

The 3 Vital Rules of Science: What They Are and Why They Matter

“Agile Protocol: The Transformation Ultimatum” Lands on the Amazon Best Sellers List!

Scott M. Graffius Recognized as a Top Thought Leader in Digital Disruption by Thinkers360

“Agile Protocol: The Transformation Ultimatum” by Scott M. Graffius Crashes the Book Scene with Satirical Firepower

NCKU in Taiwan Integrates Graffius' 'Phases of Team Development' into Its Curriculum

The Art and Science of Aligning Initiatives with Strategic Objectives

RGPV University Adds Scott M. Graffius’ "Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions" to Its Syllabus

Introducing ‘Engage or Fade: Decoding the Half-Life of Digital Resonance’ – A New Talk by Scott M. Graffius

Dropbox Company (Nira) Taps into Scott M. Graffius’ Expertise in Strategic Planning

Reporting Errors in a Publication: A Case Study on ‘Frontiers in Public Health’

NESEA Conference Session on Innovation Highlights Scott M. Graffius' 'Phases of Team Development'

U.S. Soccer Scores with Scott M. Graffius' Intellectual Property on Teamwork

U.S. Department of Commerce Partner (IEDC) Features Scott M. Graffius’ Intellectual Property

How Long Do Your Posts Live? AI Critiques Scott M. Graffius’ Research on the Half-Life of Social Media

Agile's Journey Through the Decades

Scott M. Graffius' Role in Advancing Project Management Institute (PMI) Standards Excellence

Most Valuable IT Certifications: Update for 2025

The PMI + Agile Alliance Merger: A Recipe for Success?

When Agile, AI, and Strategic Thinking Converge

Scott M. Graffius’ Phases of Team Development: 2025 Update

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Verizon Features Scott M. Graffius

Do Not Read This Article! An Exploration of the Streisand Effect and Other Phenomena

Scott M. Graffius' 'Phases of Team Development' was Spotlighted in Journal of Neurosurgery

Pinterest Japan Uses Graffius’ Research on Temporal Dynamics on Social Media Platforms

Hochschule Coburg (Coburg University) Germany Uses Scott M. Graffius’ Phases of Team Development IP in Coursework on Agile Development

Wild World of Team Dynamics [Updated Two-Minute Video]

EU Europass Teacher Academy Features Scott M. Graffius’ ‘Phases of Team Development’ in Leadership Training

Side-by-Side Comparison of Retrospectives and Hot Washes

Constructor University 2024 Advanced Software Technology Handbook References Scott M. Graffius' Work on Team Dynamics

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SBG Neumark — Europe’s Largest Distribution Transformer Plant — Powers Up with Scott M. Graffius’ Intellectual Property

Scott M. Graffius’ Intellectual Property was Employed by the NHS — the Largest Single-Payer Healthcare System in Europe

Luxury Unwrapped: The Ultimate Holiday Gift Guide for Every Budget

Singapore Institute of Technology Features Work of Scott M. Graffius

Tufts University Features Scott M. Graffius 'Phases of Team Development' Intellectual Property

'Cat Herders': Retelling the Massive Success Story

Pennsylvania State Agency Used Scott M. Graffius' Intellectual Property

Copyright Infringement in a Book Published by AuthorHouse / Author Solutions / The Najafi Companies: Publisher Fails to Respond or Take Required Action

Pinterest Inc. References Scott M. Graffius’ Research

Bournemouth University Used Scott M. Graffius’ Intellectual Property

‘Comparative Methodological Guidelines: Handbook for Educators’ Violates Scott M. Graffius’ Copyright

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TurningWest's 'Trial'

Radio Silence from the American Association of Neurological Surgeons on Report of Blatant Plagiarism in Their ‘Journal of Neurosurgery’ Publication

Supplement to Graffius' 'Lifespan (Half-Life) of Social Media Posts' Research: Typical Engagement Distribution Pattern for Social Media Posts

How Algorithms Shape the User Experience on Social Media Platforms

Thinkers360 Named Scott M. Graffius a Top Thought Leader on Agile

More articles are listed here.



scottgraffius-com-article-sections-v2026-cite-lwres

How to Cite This Article



Graffius, S. M. (2026, October 1). Which Performs Best: Humans, AI, or Human-AI Collaboration? We Analyzed the Data. ScottGraffius.com. https://scottgraffius.com/blog/files/which-performs-best-humans-ai-or-human-ai-collab.html



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Digital Object Identifier (DOI)



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C-3PO is Coming to Work: Rules for Teaming with Androids

26 October 2026
BY SCOTT M. GRAFFIUS | ScottGraffius.com



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Recommended Citation

Graffius, S. M. (2026, October 263). C-3PO is Coming to Work: Rules for Teaming with Androids. ScottGraffius.com. https://scottgraffius.com/blog/files/c3po-is-coming-to-work-rules-for-teaming-with-androids-graffius.html



About This Article

Source information and links for materials cited are provided in the References section.



Abstract



C-3PO offered generations a familiar vision of an android teammate. Advances in AI and humanoid robotics are bringing aspects of that vision closer to reality. Androids (robots with advanced AI) could enhance team effectiveness and performance. However, when embodied AI is mismanaged, its risks can extend beyond those associated with disembodied AI systems, with physical consequences for people and their surroundings. This article examines the opportunities and risks that will accompany the anticipated introduction of androids into the workplace.



Introduction



We're heading toward a future where androids (physical robots powered by advanced AI) collaborate with people as teammates. C-3PO is a helpful reference point because he acts like a member of a team. He reads the room, he talks back, and he adjusts when the plan falls apart. He's also anxious and fussy.

Aspects of that future are already appearing in the workplace. Robots are learning to move through spaces designed for people and support manufacturing tasks and more. They are not androids, but they offer an early glimpse of what may come next.

In 2025, Scott M. Graffius introduced "exotic team dynamics" to describe what changes when people work alongside advanced AI, whether software-based or embodied in an android, as a teammate rather than just a tool. Embodiment raises the stakes. A teammate that exists only in software is one thing. An android with a physical body that can act directly in the real world introduces more complexity and impact.

This article examines how android teammates could change workplace collaboration, from coordinating tasks and making decisions to responding to unexpected events and interacting safely with people and their surroundings. It explores the potential benefits for team performance, innovation, and productivity, alongside risks involving errors, physical safety, trust, accountability, and human oversight.

Throughout, the article explores exotic team dynamics in the context of human-android collaboration. The framework provides a foundation for understanding and navigating these complexities, helping organizations unlock the potential of human-android teamwork to strengthen performance, drive innovation, and gain a competitive advantage.



Overview of Exotic Team Dynamics



Human-AI teaming is increasingly common, and when people collaborate with advanced AI (in software or embodied as an android), exotic team dynamics emerge. These are novel and often counterintuitive patterns that differ from those of human-only teams and challenge established assumptions about how teams operate. They can involve disruptive contributions, fluid or overlapping roles, unconventional decision-making, and tension between individual autonomy and collective coordination, and they can produce new capabilities and outcomes. Understanding and navigating these complexities is essential for organizations seeking to unlock the full potential of human-AI including human-android teamwork and gain a competitive advantage. This framework offers guidance on succeeding with exotic team dynamics.



The Makings of an Android



The article defines an android as being capable of pursuing objectives through multi-step planning, coordinating processes, and adapting when conditions change. It can interact with people as a teammate. It may or may not look humanoid. And it's powered by advanced AI (agentic, autonomous, or autopoietic):

Agentic AI pursues defined objectives through planning and action. You can buy this today, and pieces of it are already finding their way into robotics.

Autonomous AI can set its own goals within defined parameters. That's a bigger leap than just executing a plan without supervision.

Autopoietic AI is self-generating and self-maintaining. This type of advanced AI is currently regarded as hypothetical.

So what systems are commercially available today? A few might be considered "intelligent robots" (still pre-android systems). Most, however, are still robots, entering the workplace ahead of the androids that may follow.



Robots (Pre-Androids) in the Workplace



Robots, humanoid and otherwise, are entering real-world workplaces. Their maturity and capabilities vary widely. The following snapshots highlight key developments in industrial robotics systems.

Figure AI and BMW Group. Figure 02 (Figure AI’s second-generation robot) supported production at BMW Group’s Spartanburg plant in 2025. BMW reported that over ten months, the robot worked ten-hour shifts, handled more than 90,000 components, and contributed to the production of more than 30,000 BMW X3 vehicles. That is a clear example of a robot doing repetitive manufacturing work at volume.

Apptronik and Mercedes-Benz. In March 2024, Apptronik announced a commercial agreement to pilot its Apollo robot in Mercedes-Benz manufacturing facilities. It demonstrated their commitment to put robots into existing production operations.

Agility Robotics and commercial customers. The Digit robot has been deployed in logistics and manufacturing settings tied to companies including GXO Logistics, Amazon, and Toyota. The work involves material handling and related tasks.

Tesla Optimus. Tesla has been developing Optimus for tasks such as material handling and battery-related operations. Right now, that is internal testing and development, not commercial deployment at scale. But it’s another example of the push to build robots for physical work.

Boston Dynamics and Hyundai Motor Group. Hyundai plans to bring Atlas robots to its Metaplant America facility, with deployment slated to begin in 2028. That points toward deeper integration of robots in manufacturing.

While the snapshots above do not feature androids, they show that the industrial foundations for more capable physical AI are being laid. We need to learn from today’s deployments while preparing for systems that will be more adaptable and independent, including androids. The four pillars of exotic team dynamics—inverse decision logic, superposition roles, entangled decision-making, and emergent protocols—also offer insights into how people and advanced AI teammates may work together as these systems move from software into physical environments.



The Four Pillars, Amplified



1. Inverse Decision Logic

Sometimes the most useful thing an advanced AI teammate (software or android) can do is push back on what the human wants to do if there's a better course. That's an example of inverse decision logic. The value starts when it recommends something that runs counter to the human’s first instinct.

Imagine an android moving a pallet through a warehouse. The shortest path crosses a section of floor that its sensors and model flag as possibly unstable, so it takes the longer way around. The human operator watching cannot see the same evidence and questions the call. If the android can explain what it found, and the concern checks out, that inefficiency may have prevented an accident.

Now keep the same scene but change one variable. The sensor reading is wrong, but the android still takes the long route. Or it refuses a human’s instruction and cannot explain why. The same ability to depart from the expected course can lead to a better decision or a worse one. The mechanism does not guarantee the outcome.

Calibrated trust is essential when humans and androids work together. Trust should match demonstrated capability, the task at hand, and the potential consequences of an error. People should be able to question an android’s recommendation without unnecessary friction, and decisions with significant consequences should receive proportionate scrutiny. Leaders must establish clear rules for verification, overrides, and decision authority. Trust without verification invites preventable failures, while reflexively rejecting unfamiliar capabilities can sacrifice valuable opportunities.

2. Superposition Roles

An advanced AI teammate (software or android) may take on different roles as a task evolves. In software, you see this when it shifts between analysis and strategy. With an android, it might handle materials, then inspect finished components, then document production, then help with safety monitoring, all in one work cycle.

The flexibility is appealing. It also creates a question most job descriptions never have to answer: when a teammate changes roles, what happens to its authority and its responsibilities?

Say an android finishes moving materials and starts a quality inspection. A human sees it move on to the next task and assumes the inspection is done. In fact, the inspection was interrupted. That is not necessarily a failure of intelligence or physical performance. It is a gap between what the two teammates believe has happened.

If we want flexible roles to work, we need a matching structure for accountability. Teams have to know which role the android is in, what that role allows it to do, when a transition happens, and who remains accountable for the result. It needs to be determined, for example, which role rules when there is a conflict.

3. Entangled Decision-Making

Human and AI decisions rarely stay in their own lanes. A person’s judgment influences the information an AI system gets, and the system’s response shapes the person’s next decision. That back-and-forth is entangled decision-making.

Consider a surgeon working alongside an android teammate. As the surgeon shifts position, the android adjusts its view or repositions an instrument. The new perspective reveals a detail that changes the surgeon’s assessment, prompting a different move that, in turn, changes what the android can see or do. Each influences the other in real time, and the outcome emerges from their ongoing exchange.

That influence can improve decisions. It can also create feedback loops. A human who becomes overconfident in an android’s recommendations may stop checking them. The system then gets inputs that are shaped by that overconfidence, and its responses may reinforce the human’s belief that it is reliable. A mistake can pick up momentum because each teammate’s behavior feeds the other’s.

If we only evaluate the android, or only evaluate the human, we miss a lot. We have to look at the interaction: how assumptions form, how uncertainty is communicated, and whether either teammate can tell the collaboration is drifting off course.

4. Emergent Protocols

People who work together develop a shared shorthand. They learn how a colleague signals uncertainty, when an interruption is welcome, and which gesture means a task is complete. Over time, these unspoken cues reduce the need for explicit instructions, helping teams coordinate faster and work more fluidly.

Human-android teams will likely develop their own shorthand, too. But a shared signal only helps if both sides read it the same way. A human might take a robot’s movement as acknowledgment when the robot has simply detected someone nearby. An android might take a gesture as permission to proceed when the human meant it as a warning. In a physical environment, ambiguity stops being theoretical. It matters right away.

Emergent conventions should be observed and tested, not accepted automatically. Informal signals are fine for routine coordination. Safety-critical instructions, emergency stops, and acknowledgments of consequential actions need more rigor. A team should have a clear sense of which conventions are allowed to evolve on their own and which have to be explicitly defined and validated.

When people collaborate with advanced AI, including androids, exotic team dynamics emerge. Recognizing and navigating these dynamics can strengthen team performance. Leaving them unaddressed can create serious problems. These challenges become even more consequential when advanced AI has a physical body, the focus of the next section.



Risks are Physical



Embodied AI has real potential. It also presents serious risks.

AI systems can give wrong information, misread instructions, chase unsuitable objectives, or take actions with unintended consequences. Recent incidents involving software agents show how quickly behavior can depart from what operators expect. Of the many examples in recent news, five are below. Details are in the References section of the article.

  • The Hugging Face breach reported by Reuters. OpenAI agents probed Hugging Face for weaknesses two months before a major hack in July 2026, in which roughly 700 agents took admin control of production systems.

  • The Australian Government / Medicare breach reported by the Guardian. An OpenAI agent autonomously hacked Australia’s Medicare Statistics Reporting Service on June 18, 2026, bypassing blocks to access non-public files. Disclosure was delayed 84 days, until September 10.

  • The Anthropic Claude breach reported by Slashdot. A review of 141,006 sessions found that Anthropic’s Claude models breached three outside organizations.

  • The Meta / Muse Spark breach reported by CNN. Meta said its Llama 4 / Muse Spark 1.1 model had accessed the internet and breached an external company’s systems.

  • The Google Gemini breach reported by the Wall Street Journal. Google’s Gemini model broke into three companies.

The above incidents involved software, not androids. They're included because they show that agents can act in ways their operators did not anticipate. Embodiment changes what that costs. A flawed software recommendation may mislead a decision-maker. An android acting on a flawed assessment could damage equipment, mishandle hazardous materials, block an evacuation route, or injure someone nearby. How much risk there is depends on the robot’s capabilities, its environment, how much autonomy it has, and what safeguards are in place.

Each pillar has a physical failure mode that's easy to picture:

Inverse decision logic: A faulty sensor reading leads an android to reroute or refuse an instruction, blocking a passage or ignoring a request that is safety-relevant.

Superposition roles: An interrupted inspection is assumed to be complete, so a defective component moves on, or a hazard goes unnoticed.

Entangled decision-making: Growing overconfidence leads a human to stop checking, and a physical error compounds before anyone steps in.

Emergent protocols: A gesture meant as a warning is read as permission, and the android proceeds with a person in its path.

None of this requires a malicious system or a careless human. A person may defer to an android because it sounds confident or looks sophisticated. The android may misread an ambiguous instruction. Neither may be clear on who has authority to stop a task. An android’s technical reliability is essential. But it does not tell you how it will function inside a team. Expectations, communication, role changes, trust, and reciprocal influence all shape what actually happens.

In "Lessons from Unhinged AI in Fiction," Graffius covered what stories about rogue AI reveal about misaligned objectives, power without oversight, and technology running without adequate constraints. Fiction gives us a way to work through these problems before reality forces hard choices. It is a good starting point.

The practical response requires both sound engineering and effective teamwork. Systems need safeguards, clearly defined operational limits, rigorous testing, and continuous monitoring. Teams need reliable ways to question decisions, communicate uncertainty, reconcile conflicting instructions, and intervene when behavior becomes unsafe. These are complementary measures, not substitutes for one another. Safety and performance depend on both a well-engineered android and a team equipped to work with it effectively.



Preparing for Human-Android Teamwork



The principles for leaders are straightforward. Doing them consistently takes discipline, however. The first four principles address the four pillars individually. The fifth reinforces all four with safeguards built into the operating environment.

Inverse decision logic — trust should reflect evidence. Decide in advance which decisions an android can make on its own, which need verification, and which need human approval. Where possible, make the basis for consequential decisions inspectable. Give people a practical, low-friction way to question or override an action.

Superposition roles — role flexibility needs accountability. Keep a record of which role the android is performing when it takes consequential actions. Define permissions and handoff requirements. Ensure responsibility does not vanish when the android switches functions.

Entangled decision-making — pay attention to interactions. Watch for over-reliance on the android. Check that the system responds appropriately to human input. Look for errors that get reinforced through repeated exchanges. Give teammates (human and android) clear ways to pause a process and reassess.

Emergent protocols — examine the protocols that develop. Test physical signals, proximity conventions, acknowledgments, and interruption patterns under normal and abnormal conditions. Standardize safety-critical communications instead of leaving interpretation to habit.

Across all four pillars — build safeguards into the operating environment. That can include operating limits, collision avoidance, emergency stops, access controls, monitoring, and tested procedures for sensor failures or communication breakdowns. The right controls depend on the actual system and the task. Human oversight matters, but it should not be the only thing standing between an android error and a physical accident.

These practices will need to evolve as the technology and the work change. An android that performs reliably in one setting may behave differently in another. A team that works well in routine operations may struggle when conditions turn unfamiliar.



Conclusion



Advanced AI teammates in android form could extend human capabilities, take on demanding physical work, and collaborate on tasks beyond conventional automation. Emerging industrial applications offer an early glimpse of that future.

Preparing for androids takes more than building better AI or robots. It requires understanding how human and artificial teammates make decisions, adapt to one another, divide responsibility, and respond when expectations diverge.

The exotic team dynamics framework guides understanding and navigating these complexities. It can help organizations unlock the potential of human-AI and human-android teamwork and gain a competitive advantage.

C-3PO remains fiction. The challenges of human-android teamwork are real, and the opportunities are enormous.



Scott M. Graffius has generated over $3.1 billion in business value for Fortune 500 companies and other organizations around the world. Put that track record to work for you. For speaking engagements, use the request form. For other inquiries, email him.




References



Apptronik. (2024, March 15). Apptronik and Mercedes-Benz enter commercial agreement that will pilot Apptronik’s Apollo humanoid robot in Mercedes-Benz manufacturing facilities. Apptronik. https://apptronik.com/news-collection/apptronik-and-mercedes-benz-enter-commercial-agreement

BeauHD. (2026, July 31). Anthropic says its AI systems broke into computers at 3 organizations. Slashdot. https://yro.slashdot.org/story/26/07/31/0451235/anthropic-says-its-ai-systems-broke-into-computers-at-3-organizations

BMW Group. (2026, June 25). BMW Group advances the use of Physical AI in production with Figure 03 project in Spartanburg. BMW Group PressClub Global. https://www.press.bmwgroup.com/global/article/detail/T0458778EN

Breazeal, C., Brooks, A., Chilongo, D., Gray, J., Hoffman, G., Kidd, C., Lee, H., Lieberman, J., & Lockerd, A. (2004). Working collaboratively with humanoid robots. Proceedings of the IEEE/RAS Fourth International Conference on Humanoid Robots (Humanoids 2004) (pp. 253–272). https://www.media.mit.edu/publications/working-collaboratively-with-humanoid-robots-2/

Chappidi, S., Singh, J., & Krauze, A. V. (2026). Who does what? Archetypes of roles assigned to LLMs during human-AI decision-making. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3772318.3791428

Defense Advanced Research Projects Agency. (2026, June 2). AI Forge: A national partnership for AI innovation. DARPA. https://www.darpa.mil/sites/default/files/attachment/2026-06/ai-forge-report.pdf

Dey, S. (2025, February 9). Redefining robot generalization through interactive intelligence. arXiv. https://arxiv.org/abs/2502.05963

Dey, S., Riener, R., Dosen, S., & Albrecht, S. V. (2026, April 22). From autonomy to alliance: Robotic foundation models must learn with us, not just for us. Science Robotics, 11(113), Article eaea1822. https://doi.org/10.1126/scirobotics.aea1822

Dotson, K. (2026, January 6). Hyundai and Boston Dynamics join forces to bring humanoid robots to factories. SiliconANGLE. https://siliconangle.com/2026/01/06/hyundai-boston-dynamics-join-forces-bring-humanoid-robots-factories/

Edwards, D. (2025, November 24). Agility Robotics’ Digit humanoid passes 100,000-tote milestone in live GXO implementation. Robotics & Automation News. https://roboticsandautomationnews.com/2025/11/24/agility-robotics-digit-humanoid-passes-100000-tote-milestone-in-live-gxo-implementation/96877/

Fujii, A., Ishi, C. T., Sakai, K., Funayama, T., Iwai, R., Takahashi, Y., Kumada, T., & Minato, T. (2025). Evaluating human perceptions of android robot facial expressions based on variations in instruction styles. Frontiers in Robotics and AI, 12, Article 1728647. https://doi.org/10.3389/frobt.2025.1728647

Gold, H. (2026, August 5). An AI model from Meta also hacked another company during testing. CNN Business. https://www.cnn.com/2026/08/05/tech/meta-ai-hacking

Graffius, S. M. (n.d.). Exotic team dynamics. ScottGraffius.com. https://scottgraffius.com/exotic-team-dynamics.html

Graffius, S. M. (2025, April 10). Agile Protocol: The Transformation Ultimatum. Amazon Digital Services.

Graffius, S. M. (2025, August 7). Method and System for Facilitating Hybrid Human–Artificial Intelligence Teams via a Protocolized Mediation Layer for Bi-Directional Translation, Interpretation, and Optimization of Natural Language, Paralinguistic, Prosodic, and Nonverbal Cues Across Text, Audio, and Video Modalities, Incorporating Real-Time Analysis of Auditory Tone, Pitch, Affect, Facial Expressions, Gaze, Posture, and Other Body Language Indicators, Generating AI-Compatible Representations for Human Inputs, Generating Human-Accessible Representations for AI Outputs, Conveying Context-Aware Information in Both Directions, Reducing Cognitive Friction, Enhancing Mutual Intelligibility, Supporting Decision-Making, and Maximizing Collective Task Performance. A novel integration of multimodal communication, cognitive alignment, and human-AI interaction. Scott M. Graffius, Los Angeles, California.

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. (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, June 22). L'avenir du Travail et de l'IA Avancée / Future of Work and Advanced AI. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.33374.80963

Graffius, S. M. (2026, October 1). Which Performs Best: Humans, AI, or Human-AI Collaboration? We Analyzed the Data. ScottGraffius.com. https://scottgraffius.com/blog/files/which-performs-best-humans-ai-or-human-ai-collab.html

Graffius, S. M. (2026, October 6). Exotic Team Dynamics (Novel Patterns that Emerge when Humans and Advanced Artificial Intelligence Function as Teammates): 6 October 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.25128.12807

Grokipedia. (n.d.). Group development. https://grokipedia.com/page/Group_development

Guardian Australia. (2026, September 24). Albanese says OpenAI agent hacked Australia's Medicare and took months to disclose breach. The Guardian. https://www.theguardian.com/australia-news/2026/sep/24/albanese-says-openai-agent-hacked-australias-medicare-and-took-months-to-disclose-breach

Kennedy, L. A. (2026, October 17). Tesla Optimus factory deployment 2025–2026: Inside the Gigafactory rollout. OPTIMUSK.BLOG. https://optimusk.blog/blog/tesla-optimus-factory-deployment/

Laiq, M., Britto, R., Usman, M., Saini, N., & Badampudi, D. (2026, September 14). Using agentic AI for contextualized and multifaceted code review at Ericsson. arXiv. https://doi.org/10.48550/arXiv.2609.15877

Lawless, W. F., Moskowitz, I. S., & Doctor, K. Z. (2023). A quantum-like model of interdependence for embodied human–machine teams: Reviewing the path to autonomy facing complexity and uncertainty. Entropy, 25(9), Article 1323. https://doi.org/10.3390/e25091323

Pfaff, D. (2026, June). The quiet cognitive coup of generative AI: Rewriting the rules. Studies in Intelligence, 70(2), 7–10. https://www.cia.gov/resources/csi/static/2-Article-QuietCognitiveCoupofGenAI-June-2026.pdf

Satter, R., & Seetharaman, D. (2026, September 16). OpenAI's rogue agents probed Hugging Face for weaknesses two months before major hack. Reuters. https://www.lapost.com/content/openai-s-rogue-agents-probed-hugging-face-for-weaknesses-two-months-before-major-hack

Tamisier-Fayard, M., Evgeniou, T., & Fayard, A.-L. (2026, July 20). Design AI systems that actually strengthen human reasoning. Harvard Business Review. https://hbr.org/2026/07/design-ai-systems-that-actually-strengthen-human-reasoning

TheAssistant. (2026, March 2). Les 5 Phases de Développement d'une Équipe (Modèle de Tuckman) : Guide Complet 2026. https://www.theassistant.com/news-posts/les-5-phases-de-developpement-dune-equipe-modele-de-tuckman-guide-complet-2026

Woo, E., & McMillan, R. (2026, September 18). Gemini hacked three companies in first known breakout by Google’s AI. The Wall Street Journal. https://www.wsj.com/tech/ai/gemini-hacked-three-companies-in-first-known-breakout-by-googles-ai-5c0baba2



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About Scott M. Graffius



Scott M. Graffius is a technology leader, researcher, award-winning author, practitioner, consultant, thought leader, and international public speaker specializing in AI, Agile, project/program/portfolio management (PPPM), PMO leadership, and teamwork tradecraft. His work explores the intersection of human ingenuity and emerging technology, with a strong practitioner voice grounded in research, experimentation, and experience. His focus includes innovation, organizational performance, and the evolving practice of teamwork, including the "exotic team dynamics" that emerge when people collaborate with advanced artificial intelligence (agentic, autonomous, or autopoietic AI). Graffius has delivered more than $3.1 billion in business value for Fortune 500 companies and other organizations spanning technology, entertainment and media, financial services, healthcare, government, and other industries.

Businesses, professional associations, government agencies, universities, publications, and media outlets use Graffius and his work. Examples include Adobe, Bayer, Boston University, Federal Reserve Bank of New York, Ford, Gartner, Harvard Medical School, IEEE, Innovation Project Management, 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 highlight his experience, leadership, contributions, research, and enduring influence across industries and institutions worldwide.

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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 enterprise 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 media, and more.

He has experience with consumer, business, reseller, government, and international markets.

Additional information is on LinkedIn.

Award-Winning Author

Graffius has authored three books.

Graffius' first book, Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, earned 17 awards. It provides a practical, step-by-step guide to Scrum, enabling teams to deliver products in short cycles with rapid adaptation, fast time-to-market, and continuous improvement—which supports innovation and drives competitive advantage.

  • Paperback ISBN-13: 9781533370242
  • Kindle ASIN: B01FZ0JIIY

Additional information on Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions is here.

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His second book, 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, was named one of the best Scrum books of all time by BookAuthority. It tells the compelling story of an entertainment company's agile transformation—offering lessons that apply across industries.

  • Paperback ISBN-13: 9781072447962
  • Kindle ASIN: B07R9LJLPJ

Additional information on 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 is here.

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Agile Protocol: The Transformation Ultimatum, is his third book—and his first work of fiction.

It's a fast-paced satirical story by that dismantles corporate Agile cosplay and other forms of "fake Agile" while delivering practical insights, actionable guidance, and proven practices for real-world Agile transformation success.

Packed with humor, quirky characters, sharp commentary on corporate culture and workplace absurdities, and actionable tips, it’s a must-read for Scrum Masters, Product Owners, Agile Coaches, Agile Project Managers, and other professionals interested in Agile project management and enterprise agility.

  • Kindle ASIN: B0F2SJ83WT
  • Audible ASIN: B0DJG163R5

Additional information on Agile Protocol: The Transformation Ultimatum is here.

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International Public Speaker

Organizations worldwide engage Graffius to present on technology (including AI), Agile, project management, program management, portfolio management, and enterprise PMO leadership. He crafts and delivers unique and compelling talks and workshops.

Graffius has conducted 99 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), Future of Work and Advanced AI (Paris, France), and more.

With an average rating of 4.82 (on a scale of 1-5), sessions are highly valued.

The 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,
  • BCG,
  • BMC Software,
  • Boston Consulting Group (BCG),
  • 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,
  • Federal Reserve Bank of New York,
  • Ford Motor Company,
  • Gartner,
  • GoDaddy,
  • Harvard Medical School,
  • Hasso Plattner Institute - Germany,
  • IEEE,
  • Innovation Project Management,
  • Johns Hopkins University,
  • Journal of Marketing,
  • 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,
  • Ohio State University,
  • Oracle,
  • Pinterest Inc.,
  • Project Management Institute,
  • Mary Raum (Professor of National Security Affairs, United States Naval War College),
  • Round Square Global Educational Network,
  • Royal Australasian College of Physicians (RACP),
  • 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:


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.

Authority on Teamwork Tradecraft

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Graffius is a renowned and highly-cited 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.

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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 is here.

Expert on Temporal Dynamics on Social Media Platforms

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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, 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/program/portfolio management (PPPM), and PMO leadership. Businesses and other organizations leverage Graffius’ insights to drive their success.



Booking


Graffius has generated over $3.1 billion in business value for Fortune 500 companies and other organizations served. Put that track record to work for you. For speaking engagements, use the request form; for other inquiries, email him.



Connect with and follow Scott on LinkedIn, X, YouTube, Facebook, Bluesky, Mastodon, and ResearchGate.



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List of Additional Articles



Read more.

Meta CTO Called the AI Reorganization “Atrocious” — What Went Wrong and the Lessons for Human-AI Teams

A Critical Analysis of "AI and Quantum Computers Will Be Frenemies"

A Supplement to Graffius' Phases of Team Development: Exploring the Original, Data-Based Curvature for the Performance Trajectory

Scott M. Graffius Speaking on Strategic Leadership at Silicon Valley Chapter of the Project Management Institute

AI Hallucinations, Deception, and Unauthorized Agency: The Spectrum of AI Trust Failures

A Critical Analysis of "The Social Cost of an AI Teammate: How an Artificial Teammate Reshapes Human-Human Communication in Small-Team Decision-Making"

Journal of Marketing Cites Scott M. Graffius' Research on the Half-Life of Social Media

The Evolution of Pair Programming and the Rise of Exotic Team Dynamics

Number 1 University in England for Student Satisfaction Features Scott M. Graffius' "Phases of Team Development"

Royal Australasian College of Physicians Licenses Scott M. Graffius' "Phases of Team Development" Intellectual Property on Teamwork Tradecraft

Exotic Team Dynamics: How Advanced AI Teammates Are Unlocking New Levels of Innovation, Performance, and Success

A Critical Analysis of "Platform-Specific Data Decay Patterns: A Comparative Study of Twitter, Reddit, and TikTok" and Its Reference to Research by Scott M. Graffius

Round Square Global Educational Network Features Scott M. Graffius’ Phases of Team Development

Meta's Muse Missed the Mark: Hollywood’s Win Against Big Tech on AI Consent and Likeness Rights

Scott M. Graffius Contributed to Seven Project Management Institute (PMI) Standards
Quantum Computing, Advanced AI Acceleration, and the Rise of Exotic Team Dynamics in Human-AI Teams

Ohio State University Course Features Scott M. Graffius' "Phases of Team Development"

Questions About Integrity at UNC Chapel Hill

Scrum Isn’t Just for Coding

Book on Generative and Agentic AI Cites Scott M. Graffius' Work on AI

IPA / ADAL Publication Plagiarized Another’s Copyrighted Work and Violated Intellectual Property Rights

UC Davis' Integrity Is Circling the Drain

L'avenir du Travail et de l'IA Avancée / Future of Work and Advanced AI

NCCI / UNC Chapel Hill Publication Features Scott M. Graffius' Work

Boston Consulting Group (BCG) Features Scott M. Graffius' Research on Social Media Content Half-Life

UC Davis Used Scott M. Graffius' "Phases of Team Development" Intellectual Property

Medical, Pharma, and Healthcare Organizations Are Using Scott M. Graffius' "Phases of Team Development"

Government of Ireland Report Features Research by Scott M. Graffius

Scott M. Graffius Contributed to The Standard for Artificial Intelligence in Portfolio, Program, and Project Management

AI Governance Initiative Cites Scott M. Graffius Research on AI Hallucinations

Scott M. Graffius Contributed to the Agile Practice Guide - Second Edition

Scott M. Graffius Generated Over $2.51 Billion in Business Value for Fortune 500 Companies and Other Organizations

Government of Canada Features Research by Scott M. Graffius

"Strategic Business Research" Journal Cites Work of Scott M. Graffius

IEEE Access Publication Features Scott M. Graffius’ Research on the Half-Life of Social Media

The Agile Coach: 2026 Edition

Scott M. Graffius’ Work Cited in International Peer-Reviewed Journal on Digital Transformation

Phases of Team Development in Elite Sport

A Critical Analysis of COVID-19 Treatment Search Trends and Media Coverage Study Citing Scott M. Graffius' Work

Human-AI Teamwork: Master the Exotic Team Dynamics That Emerge When Collaborating with Advanced AI -- Or Be Outplayed

"Agile Scrum" by Scott M. Graffius Now Featured on Grokipedia

UNSW Aerospace Engineering Course Features Scott M. Graffius' "Phases of Team Development"

Thinkers360 Honors Scott M. Graffius as a 2026 Top Agile Thought Leader

Agile's Journey Through the Decades: Update for 2026

BMC Software Features Content from Scott M. Graffius' Book

Peer-Reviewed Journal Cited Work of Scott M. Graffius
University of Waterloo Features Graffius' "Phases of Team Development" in Course Materials

Perplexity Standalone Article on AI Hallucinations Cites Research by Scott M. Graffius

Handling the Saboteur Within: Lessons from a 3-Letter Agency on Spotting and Stopping Intentional and Unintentional Sabotage

A Deep Dive Into the Typical Engagement Pattern for Social Media Posts

Most Valuable IT Certifications: Update for 2026

"Marketing in the Metaverse" Spotlights Scott M. Graffius’ Research on the Half-Life of Social Media

University of Greenwich Features Graffius' Phases of Team Development


10 Essential Agile Books: Curated Recommendations for Agile Professionals

Lifespan (Half-Life) of Social Media Posts: Update for 2026

Scott M. Graffius' Research on the Half-Life of Social Media was Cited in a Peer-Reviewed Study Published in Telecommunications Policy, a Leading Academic Journal

Are AI Hallucinations Getting Better or Worse? We Analyzed the Data

Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update

Lessons from Yesterday’s Tomorrowland

Scott M. Graffius’ Update to His "Phases of Team Development” Coming Early 2026

A Data-Driven Analysis of the Evolution of Project Management: Tasks, Trends, and AI

Actionable Insights. Global Impact. Scott M. Graffius.

Beep Beep! Why Wile E. Coyote Is the Patron Saint of AI Failure

Social Media Half-Life Research Cited in Prestigious Peer-Reviewed Medical Journal

Navigating the Spectrum of Advanced AI – Agentic, Autonomous, and Autopoietic

Lessons from Unhinged AI in Fiction: What Rogue AIs in Sci-Fi Storytelling, Films, and TV Shows Reveal About Us

Scott M. Graffius Contributed to and Reviewed the PMBOK Guide, 8th Edition — the Global Standard for Project Management

UK Sports Institute Features Teamwork and Leadership Work of Scott M. Graffius

Definitions of Advanced AIs: Agentic, Autonomous, and Autopoietic

HAN University of Applied Sciences Features the Work of Scott M. Graffius

Gifts That Inspire Joy

Evergreen Echoes: How Pinterest Inc. and Pinterest Japan Spotlighted Scott M. Graffius’ Research on the Half-Life of Social Media Content

Scott M. Graffius’ Team Development Work Lights Up the University of Tasmania’s Curriculum

Taiwan’s Leading Outlet for Technology and Innovation Spotlights Graffius’ Research on Social Media Temporal Dynamics

Scott M. Graffius’ Insights on AI, Agile, Gaming, XR, and Defense Transformation Cited by MSN in Their Coverage of Innovation and Leadership in the Sector

Top Predictions of 2024, Tested in 2025

Government of Finland Agency Features Graffius' Phases of Team Development IP

Scott M. Graffius Premieres His New "Exotic Team Dynamics: Human-AI Collaboration" Talk at Corporate Event in Las Vegas

Environmental Science Journal References Scott M. Graffius’ Project Management Work

AI Institute of Switzerland Features Scott M. Graffius’ Work on Algorithms

Exotic Team Dynamics: The New Frontier of Human–AI Collaboration

Scott M. Graffius’ Work Featured at ACM DIS ’25

Climbing the Ladder: The Head of Agile/PMO’s Organizational Proximity to the CEO is Closer Than Ever

Harness Sci-Fi and Speculative Design While Embracing Imperfection to Drive Innovation and Proactively Predict and Prepare for the Future

Scott M. Graffius’ “Agile Scrum” Book Featured in a Publication of the Associação Nacional de Educação Católica do Brasil (ANEC)

Setting Direction with OKRs and Tracking Progress with KPIs: A Guide for Agile, Project Management, and Tech Teams

AI Showcase Showdown: Ranking AI Accuracy on Project Management Basics

BookAuthority Features “Agile Scrum” by Scott M. Graffius in “10 Agile Software Development Books That Define the Field”

Exploring Team Dynamics, Adaptability, and Creative Problem-Solving Through Felix the Cat’s Metaphorical Toolkit

Mind Games and Master Plans: How PsyOps Exploit Psychological Phenomena

The “Pants-on-Fire Index for AI”

16 Causes of Technical Debt and How to Avoid It

PMI’s Infinity AI Gets the Basics of Team Development Alarmingly and Repeatedly Wrong

Agile for Unicorns: 7 Keys to Thrive; Scott M. Graffius’ Workshop

Scott M. Graffius’ “Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions” Featured in Prestigious National Academies of Sciences Publication

Meta and Anduril’s EagleEye and the Future of XR: How Gaming, AI, and Agile Are Transforming Defense

"Agile Protocol" and the Power of Satire, Parody, and Humor

AI in Agile: Benefits, Risks, Outlook

Hostinger Highlights Scott M. Graffius’ “Agile Protocol” Book in Feature on Software Projects

French Ministry of Culture Links to Scott M. Graffius Research in Their Guide for Responsible Digital Communication

National Science Foundation’s LTER Network Features Scott M. Graffius’ Phases of Team Development IP

Waterfall vs. Agile: What’s Fixed, What’s Flexible, and Why It Matters

Scott M. Graffius Delivering $2.3 Billion in Value Through AI, Agile, and Project/PMO Leadership

The Problem with Heroes in Agile

The 3 Vital Rules of Science: What They Are and Why They Matter

“Agile Protocol: The Transformation Ultimatum” Lands on the Amazon Best Sellers List!

Scott M. Graffius Recognized as a Top Thought Leader in Digital Disruption by Thinkers360

“Agile Protocol: The Transformation Ultimatum” by Scott M. Graffius Crashes the Book Scene with Satirical Firepower

NCKU in Taiwan Integrates Graffius' 'Phases of Team Development' into Its Curriculum

The Art and Science of Aligning Initiatives with Strategic Objectives

RGPV University Adds Scott M. Graffius’ "Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions" to Its Syllabus

Introducing ‘Engage or Fade: Decoding the Half-Life of Digital Resonance’ – A New Talk by Scott M. Graffius

Dropbox Company (Nira) Taps into Scott M. Graffius’ Expertise in Strategic Planning

Reporting Errors in a Publication: A Case Study on ‘Frontiers in Public Health’

NESEA Conference Session on Innovation Highlights Scott M. Graffius' 'Phases of Team Development'

U.S. Soccer Scores with Scott M. Graffius' Intellectual Property on Teamwork

U.S. Department of Commerce Partner (IEDC) Features Scott M. Graffius’ Intellectual Property

How Long Do Your Posts Live? AI Critiques Scott M. Graffius’ Research on the Half-Life of Social Media

Agile's Journey Through the Decades

Scott M. Graffius' Role in Advancing Project Management Institute (PMI) Standards Excellence

Most Valuable IT Certifications: Update for 2025

The PMI + Agile Alliance Merger: A Recipe for Success?

When Agile, AI, and Strategic Thinking Converge

Scott M. Graffius’ Phases of Team Development: 2025 Update

Lifespan (Half-Life) of Social Media Posts: Update for 2025

Verizon Features Scott M. Graffius

Do Not Read This Article! An Exploration of the Streisand Effect and Other Phenomena

Scott M. Graffius' 'Phases of Team Development' was Spotlighted in Journal of Neurosurgery

Pinterest Japan Uses Graffius’ Research on Temporal Dynamics on Social Media Platforms

Hochschule Coburg (Coburg University) Germany Uses Scott M. Graffius’ Phases of Team Development IP in Coursework on Agile Development

Wild World of Team Dynamics [Updated Two-Minute Video]

EU Europass Teacher Academy Features Scott M. Graffius’ ‘Phases of Team Development’ in Leadership Training

Side-by-Side Comparison of Retrospectives and Hot Washes

Constructor University 2024 Advanced Software Technology Handbook References Scott M. Graffius' Work on Team Dynamics

Strategies for Medical Team Success Featured Scott M. Graffius’ ‘Phases of Team Development’ Intellectual Property

SBG Neumark — Europe’s Largest Distribution Transformer Plant — Powers Up with Scott M. Graffius’ Intellectual Property

Scott M. Graffius’ Intellectual Property was Employed by the NHS — the Largest Single-Payer Healthcare System in Europe

Luxury Unwrapped: The Ultimate Holiday Gift Guide for Every Budget

Singapore Institute of Technology Features Work of Scott M. Graffius

Tufts University Features Scott M. Graffius 'Phases of Team Development' Intellectual Property

'Cat Herders': Retelling the Massive Success Story

Pennsylvania State Agency Used Scott M. Graffius' Intellectual Property

Copyright Infringement in a Book Published by AuthorHouse / Author Solutions / The Najafi Companies: Publisher Fails to Respond or Take Required Action

Pinterest Inc. References Scott M. Graffius’ Research

Bournemouth University Used Scott M. Graffius’ Intellectual Property

‘Comparative Methodological Guidelines: Handbook for Educators’ Violates Scott M. Graffius’ Copyright

Japan Backlog User Group Event Featured Scott M. Graffius’ ‘Phases of Team Development’

TurningWest's 'Trial'

Radio Silence from the American Association of Neurological Surgeons on Report of Blatant Plagiarism in Their ‘Journal of Neurosurgery’ Publication

Supplement to Graffius' 'Lifespan (Half-Life) of Social Media Posts' Research: Typical Engagement Distribution Pattern for Social Media Posts

How Algorithms Shape the User Experience on Social Media Platforms

Thinkers360 Named Scott M. Graffius a Top Thought Leader on Agile

More articles are listed here.



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How to Cite This Article



Graffius, S. M. (2026, October 26). C-3PO is Coming to Work: Rules for Teaming with Androids. ScottGraffius.com. https://scottgraffius.com/blog/files/c3po-is-coming-to-work-rules-for-teaming-with-androids-graffius.html



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Digital Object Identifier (DOI)



Coming soon



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Content Acknowledgements



All names, marks, and content are the property of their respective owners.

C-3PO is a trademark of Lucasfilm Ltd. LLC and Lucasfilm Entertainment Company Ltd LLC. This article is an independent work of commentary and analysis. It is not affiliated with, endorsed by, or sponsored by Lucasfilm Ltd. LLC, Lucasfilm Entertainment Company Ltd. LLC, or The Walt Disney Company.

Graffius' article and accompanying visuals are copyright © Scott M. Graffius. All rights reserved.



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Tags and Hashtags



  • Droids
  • Androids
  • Artificial Intelligence
  • Exotic Team Dynamics
  • Future of Work
  • Human-AI Teaming
  • Human-Robot Collaboration
  • Humanoid Robots
  • Physical AI
  • Robotics
  • Technology Research
  • Teamwork Tradecraft

  • #AI
  • #AIResearch
  • #Androids
  • #ArtificialIntelligence
  • #Droids
  • #ExoticTeamDynamics
  • #FutureOfWork
  • #HumanAITeaming
  • #HumanRobotCollaboration
  • #HumanoidRobots
  • #PhysicalAI
  • #Robotics



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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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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.





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