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

21 November 2025

BY SCOTT M. GRAFFIUS | ScottGraffius.com

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Recommended Citation

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

Introduction

Scott M. Graffius has explored the transformative frontier of human-AI collaboration through a series of articles and talks. It began with Exotic Team Dynamics: The New Frontier of Human–AI Collaboration (August 8, 2025). In that piece, he conveyed that advanced AI is no longer just a tool. It is emerging as a genuine teammate, creating entirely new “exotic team dynamics” patterns inspired by quantum concepts such as inverse decision logic, superposition roles, entangled decision-making, and emergent protocols.

He premiered a talk on this topic, Exotic Team Dynamics: Human-AI Collaboration, at a private corporate leadership retreat in Las Vegas on August 22, 2025, where he offered leaders actionable insights for successfully designing and scaling these teams. He published an article about it the same day.

Graffius then released Definitions of Advanced AIs (October 29, 2025) to bring greater clarity and refinement to the terminology.

Additionally, to balance the referenced opportunities with risks, Graffius published Lessons from Unhinged AI in Fiction (November 19, 2025) to highlight potential threats, drawing on sobering warnings from HAL 9000, Skynet, and other fictional AI. Top lessons include:

AI is a mirror of human flaws, desires, and fears.
Misaligned goals and a lack of oversight are a recipe for disaster.
Complexity and autonomy create unpredictability.
Ensuring humans act responsibly and ethically is central to realizing safe and trustworthy AI systems.

Here, Graffius presents an enhanced side-by-side comparison of multiple aspects of the current state of agentic, autonomous, and autopoietic AI. A visual is embedded below and serves as the centerpiece of this article.

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To request a high-resolution version of the above visual, email Scott.

A Clear Progression: Agentic, Autonomous, and Autopoietic AI

Agentic AI is commercially available and in use. Systems such as Anthropic Claude with Computer Use, Microsoft Copilot Studio Custom Agents, and Salesforce Agentforce can take a human-defined objective, independently plan multi-step actions, coordinate multiple processes and tools, and adjust strategies as conditions change. These systems are semi-autonomous overall, yet highly autonomous in execution. That’s what today’s enterprises are deploying to reshape knowledge work.

From Fiction: The Ship’s Computer from TV's Star Trek is an agentic AI, capable of performing tasks and acting on behalf of humans to achieve specific goals, but not autonomous or autopoietic because it follows human instructions and cannot make independent decisions or self-sustain.

Aspects of agentic AI follow.

Definition: Agentic AI is an advanced AI capable of pursuing defined objectives independently by planning multi-step actions, coordinating multiple processes, and adjusting strategies in response to changing conditions. It is semi-autonomous overall but highly autonomous in execution.
Examples of commercially available systems: Adept Frontier Agents, Anthropic Claude with Computer Use, Microsoft Copilot Studio Custom Agents, and Salesforce Agentforce
Fictional examples: The Ship’s Computer from TV's Star Trek
Goal source: External: Defined by humans
Core behavior: Decomposes tasks, orchestrates workflows, plans next steps, collaborates with user when needed
Learning/adaptation: Learns to improve planning/execution; adapts strategies to dynamic contexts
Structure/coordination: Multi-process, multi-step orchestration (“agentic loops” such as reflect–critique–act)
Human oversight/intervention: Humans define objectives; AI executes autonomously but coordinates as needed
User role: Collaborator → Consultant → Approver
User involvement: Limited user involvement
AI autonomy: AI has limited autonomy
Governance risk: Objective misalignment; challenges in multi-agent orchestration and correctness
Critical controls: Invocation or approval before actions

The aspects are also shown in the visual above.

Autonomous AI—defined as AI capable of independent operation without direct human control and able to set or adjust its own goals within defined or evolving parameters—does not yet exist in a commercial product. The closest real-world examples (Waymo driverless taxis, Google DeepMind’s data-center cooling optimization, certain industrial robots) remain rigidly bound by human-set objectives and operational domains. They exhibit high but bounded autonomy, not the broad, goal-evolving independence the definition requires.

From Fiction: Rosie the Robot from TV's The Jetsons is an autonomous AI, capable of independent action and decision-making on behalf of humans, but not autopoietic because she does not self-produce, self-replicate, or maintain her own existence beyond the functions programmed into her.

Aspects of autonomous AI follow.

Definition: Autonomous AI is an advanced AI capable of independent operation and decision-making without direct human control or intervention. It is distinguished from less advanced systems by its self-regulation, capacity to set or adjust goals, and ability to act on those goals within defined or evolving parameters.
Examples of commercially available systems: As defined, Autonomous AI does not yet exist in a commercial product; research prototypes from Google DeepMind, OpenAI, and xAI are close and are not yet commercially available
Fictional examples: Rosie the Robot from TV’s The Jetsons
Goal source: Internal or external: Defined by human or AI; AI may update goals
Core behavior: Acts independently; adapts to environment; may change goals to meet conditions
Learning/adaptation: Learns from environment; updates decisions or goal-selection processes
Structure/coordination: Typically, a single system with internal autonomy
Human oversight/intervention: Minimal ongoing oversight; human involvement primarily for exceptions or risk boundaries
User role: Approver → Observer
User involvement: Very limited user involvement
AI autonomy: AI has high but bounded autonomy
Governance risk: Goal drift; difficulty constraining evolving autonomous behavior
Critical controls: Conditions for approval by human

The aspects are also shown in the visual above.

Autopoietic AI remains purely hypothetical and experimental. It would be a self-generating, self-maintaining, recursively-organizing system that continuously regenerates its own structure, rules, and operational boundaries while sustaining its functional identity—resembling biological life far more than software. No such system is commercially available, and oversight of it would be highly limited or unnecessary because the system itself would evolve its own rules and structure.

From Fiction: The Machines from the film The Matrix are autopoietic AI, capable of self-production, self-replication, and maintaining their own existence independently of humans, while also exhibiting autonomous decision-making and goal-directed behavior.

Aspects of autopoietic AI follow.

Definition: Autopoietic AI is an advanced, experimental AI defined by self-generating, self-maintaining, and self-adaptive processes. Unlike other AIs, it features a recursive organization. It continually regenerates its structure, rules, and boundaries, sustaining its functional identity amid changing environments.
Examples of commercially available systems: Autopoietic AI is not currently commercially available
Fictional examples: The Machines from the film The Matrix
Goal source: Self-generated: AI determines its own structure, rules, and aims
Core behavior: Recursively self-producing; maintains its own internal organization and boundaries
Learning/adaptation: Deep recursive adaptation; the system revises its own organizational structure
Structure/coordination: Highly recursive, self-producing architecture resembling autopoietic biological systems
Human oversight/intervention: Oversight highly limited or unnecessary; system evolves its own rules and structure
User role: Hypothetically, non-participant
User involvement: Potentially, no user involvement
AI autonomy: AI has complete autonomy
Governance risk: High unpredictability due to structural self-generation; difficult to constrain
Critical controls: Emergency off switch (theoretical)

The aspects are also shown in the visual above.

Goals, Roles, and Controls

The source of goals marks the clearest dividing line: Agentic AI always starts with external human-defined objectives; Autonomous AI can update or set its own goals within parameters (human- or AI-derived); Autopoietic AI self-generates its aims, structure, and very existence.

Human roles shift accordingly—from active collaborator/approver in agentic systems, to distant observer in autonomous ones, to potentially no role at all (non-participant) in an autopoietic future. Governance risk escalates from objective misalignment and orchestration challenges today to goal drift tomorrow, and ultimately, high unpredictability and near-impossibility of constraint when systems begin to structurally regenerate themselves.

Even the critical controls tell the story. Today, we require invocation or approval before major actions; true autonomous systems would rely on conditional human approvals for exceptions. And for autopoietic systems, the only remaining idea is a theoretical “emergency off switch”—widely acknowledged to be unreliable or evadable once a system can rewrite its own code and replicate elsewhere.

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Conclusion

We don’t need to slow progress; we need to steer it.

Organizations that master agentic human-AI teams today—with crystal-clear human-defined goals, approval gates, transparent reasoning traces, and ethical rituals—will be the ones best prepared for autonomous capabilities tomorrow and best positioned to implement the guardrails that prevent autopoietic risk the day after.

The gradient from heavy user involvement to near-total AI autonomy is not a distant horizon—it’s the road we’re already on. Those who navigate it wisely—embracing collaboration, transparency, and guardrails—will shape the future rather than be shaped by it.

Businesses, professional associations, government agencies, and universities worldwide engage Scott M. Graffius for consultation and speaking engagements. His sessions on human and human-AI teams—including the "exotic team dynamics" that emerge—deliver fresh insights and actionable strategies for success. Complete a request form or email him today.

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

26 June 2026

BY SCOTT M. GRAFFIUS | ScottGraffius.com

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Recommended Citation

Graffius, S. M. (2026, June 26). Book on Generative and Agentic AI Cites Scott M. Graffius' Work on AI. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.24573.32488

Scott M. Graffius helps organizations achieve breakthrough performance and generate billions in business value through his leadership. Graffius and his work in AI, Agile, teamwork tradecraft (both human teams and human-AI teams, including the "exotic team dynamics" which emerge with advanced AI), and temporal dynamics in social media have been featured, cited, and used by leading businesses, professional associations, government agencies, universities, publications, media outlets, and others around the world. Examples include:

Adobe
American Management Association
Bayer
Boston Consulting Group (BCG)
Boston University
Cisco
École Polytechnique Fédérale de Lausanne
Ford
Gartner
GoDaddy
Government of Canada
Harvard Medical School
Hasso-Plattner-Institut für Digital Engineering GmbH
IEEE
Innovation Project Management
Johns Hopkins University
Maximizing LinkedIn for Business Growth
Microsoft
MSN
National Academy of Sciences
Oracle
Pinterest Inc.
Project Management Institute
Tufts University
UK Sports Institute
University of California, San Diego (UC San Diego)
U.S. Tennis Association
Verizon
Yale University
among many others.

That list now includes Building a Business Empire by Utilizing Generative AI: How Agentic AI Turns Retail & Logistics Startups Into Success Stories, published by NuovoNova Ltd. and authored by Marc Stanford and Carl Vincent Sutton. The book cites Graffius' article, "AI is a Team Sport: A Confluence of Diverse Technical and Soft Skills are Crucial for Success." Excerpts are shown below.

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About the authors of the book: Marc Stanford holds an MSc in Advanced Computer Science and a PhD in Natural Language Processing and has spent more than a decade exploring the transformative potential of AI technologies. Carl Vincent Sutton is a financial expert with an MBA in Investment Management and a Master of Finance in Asset Management. His career in global equity markets included rising from stockbroker to board member, most recently serving as Vice President in the Private Equity and Hedge Fund division of a U.S. investment bank.

Their book explores how generative AI and agentic AI are transforming retail and logistics by enabling personalized shopping experiences, real-time demand forecasting, supply chain optimization, and logistics automation that reduces costs and delivery times. It features case studies drawn from Walmart, Home Depot, Alibaba, Tesco, DHL, FedEx, and other companies.

Graffius' "AI is a Team Sport: A Confluence of Diverse Technical and Soft Skills are Crucial for Success" was informed by his work on AI projects as well as research and coverage from DARPA, Exceptional Agility, IBM, IEEE, Intel, MIT, Microsoft, Nvidia, Samsung, Software Engineering Institute, Stanford University, United States Artificial Intelligence Institute, and others. The piece covers the significance of well-rounded AI teams, highlighting that both soft and technical skills are critical to success. Communication, collaboration, and leadership are a few examples of soft skills (also known as core skills, interpersonal skills, people skills, power skills, or transferable skills). AI frameworks, data science, and algorithms are a few examples of technical skills (sometimes called hard skills). Graffius wrote, "AI is a team sport that thrives on the confluence of soft skills and technical skills. By recognizing and embracing this synergy, organizations can unlock the full potential of AI, delivering innovative solutions that address real-world challenges and have a positive impact on the world."

The inclusion of Graffius' work in Building a Business Empire by Utilizing Generative AI: How Agentic AI Turns Retail & Logistics Startups Into Success Stories underscores the practical relevance of his research for entrepreneurs, executives, and other leaders building AI-enabled organizations. Links to the book and to Graffius' AI-related publications are provided in the bibliography below.

Scott M. Graffius has generated over $2.51 billion in business value for Fortune 500 companies and other organizations around the world. Put that track record to work for you. For speaking engagements, use the request form; for other inquiries, email him.

Bibliography

Graffius, S. M. (n.d.). Articles Index. ScottGraffius.com. https://scottgraffius.com/articles-index.html

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

Graffius, S. M. (2023, May 1). AI is a Team Sport: A Confluence of Diverse Technical and Soft Skills are Crucial for Success. ScottGraffius.com. https://www.scottgraffius.com/blog/files/successful-ai-teams.html

Graffius, S. M. (2025, August 8). Exotic Team Dynamics: The New Frontier of Human–AI Collaboration. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18048.49921

Graffius, S. M. (2025, August 22). Scott M. Graffius Premieres His New "Exotic Team Dynamics: Human-AI Collaboration" Talk at Corporate Event in Las Vegas. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.34380.07047

Graffius, S. M. (2025, October 29). Definitions of Advanced AIs: Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.10025.66402

Graffius, S. M. (2025, November 19). Lessons from Unhinged AI in Fiction: What Rogue AIs in Sci-Fi Storytelling Reveal. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.29673.35687

Graffius, S. M. (2025, November 21). Navigating the Spectrum of Advanced AI – Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.21284.74882

Graffius, S. M. (2025, November 21). This is What Happens When Advanced AI Joins Your Team [Presentation]. Corporate event, Paris, France.

Graffius, S. M. (2025, December 1). Beep Beep! Why Wile E. Coyote Is the Patron Saint of AI Failure. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.35578.15048

Graffius, S. M. (2025, December 9). A Data-Driven Analysis of the Evolution of Project Management: Tasks, Trends, and AI. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.25079.28328

Graffius, S. M. (2025, December 25). Navigating the Spectrum of Advanced AI – Agentic, Autonomous, and Autopoietic [Video]. YouTube. https://www.youtube.com/watch?v=DtGgD-0gcv8

Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601

Graffius, S. M. (2026, March 23). Human-AI Teamwork: Master the Exotic Team Dynamics That Emerge When Collaborating with Advanced AI — Or Be Outplayed. ScottGraffius.com. https://scottgraffius.com/blog/files/human-ai-teamwork-master-the-emergent-exotic-team-dynamics-or-be-outplayed.html

Graffius, S. M. (2026, June 22). L'avenir du Travail et de l'IA Avancée / Future of Work and Advanced AI. ScottGraffius.com. https://scottgraffius.com/blog/files/lavenir-du-travail-et-de-lia-avancee.html

Mercier, C. (2026, April 8). Life Sciences & M&A | Industry Intelligence [LinkedIn article]. https://www.linkedin.com/pulse/life-sciences-ma-industry-intelligence-caroline-mercier-hcxue/

Patel, K. (2026, February 7). What is agentic reasoning? Learn Agentic. https://learnagentic.substack.com/p/what-is-agentic-reasoning

Skywork AI. (n.d.). AI team development stages. https://skywork.ai/slide/en/ai-team-development-stages-2033809730980769792

Stanford, M., & Sutton, C. V. (2025). Building a Business Empire by Utilizing Generative AI: How Agentic AI Turns Retail & Logistics Startups into Success Stories. NuovoNova Ltd.

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

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About Scott M. Graffius

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Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.

He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 99 conferences and other events across 25 countries.

He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.

Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.

The following sections provide additional information on his experience, contributions, and influence.

Experience

Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.

Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.

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

Award-Winning Author

Graffius has authored three books.

Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.

International Public Speaker

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

With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.

The speaker engagement request form is here.

Thought Leadership and Influence

Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:

Adobe,
American Management Association,
Amsterdam Public Health Research Institute,
Bayer,
BMC Software,
Boston University,
Broadcom,
Cisco,
Coburg University of Applied Sciences and Arts - Germany,
Computer Weekly,
Constructor University - Germany,
Data Governance Success,
Deimos Aerospace,
DevOps Institute,
Dropbox,
EU's European Commission,
Ford Motor Company,
Gartner,
GoDaddy,
Harvard Medical School,
Hasso Plattner Institute - Germany,
IEEE,
Innovation Project Management,
Johns Hopkins University,
Journal of Neurosurgery,
Lam Research (Semiconductors),
Leadership Worthy,
Life Sciences Trainers and Educators Network,
London South Bank University,
Microsoft,
MSN,
NASSCOM,
National Academy of Sciences,
New Zealand Government,
Oracle,
Pinterest Inc.,
Project Management Institute,
Mary Raum (Professor of National Security Affairs, United States Naval War College),
SANS Institute,
SBG Neumark - Germany,
Singapore Institute of Technology,
Torrens University - Australia,
TBS Switzerland,
Tufts University,
UC San Diego,
UK Sports Institute,
University of Galway - Ireland,
US Department of Energy,
US National Park Service,
US Soccer,
US Tennis Association,
Verizon,
Wrike,
Yale University,
and many others.

Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:

The Standard for Artificial Intelligence in Portfolio, Program, and Project Management
Agile Practice Guide – Second Edition
A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Eighth Edition
A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Sixth Edition
The Standard for Program Management – Fourth Edition
Practice Standard for Work Breakdown Structures – Second Edition
The Practice Standard for Project Estimating – Second Edition

He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.

Acclaimed Authority on Teamwork Tradecraft

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Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."

The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.

Expert on Temporal Dynamics on Social Media Platforms

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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 (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.

The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.

Education and Professional Certifications

Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:

Certified SAFe 6 Agilist (SA),
Certified Scrum Professional - ScrumMaster (CSP-SM),
Certified Scrum Professional - Product Owner (CSP-PO),
Certified ScrumMaster (CSM),
Certified Scrum Product Owner (CSPO),
Project Management Professional (PMP),
Lean Six Sigma Green Belt (LSSGB), and
IT Service Management Foundation (ITIL).

He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).

Advancing AI, Agile, and Project/PMO Management

Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.

Discover Scott’s Books

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

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List of Additional Articles

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How to Cite This Article

Graffius, S. M. (2026, June 26). Book on Generative and Agentic AI Cites Scott M. Graffius' Work on AI. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.24573.32488

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Digital Object Identifier (DOI)

DOI: 10.13140/RG.2.2.24573.32488

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Content Acknowledgements

Building a Business Empire by Utilizing Generative AI: How Agentic AI Turns Retail & Logistics Startups into Success Stories book by Marc Stanford and Carl Vincent Sutton cites Scott M. Graffius’ “AI is a Team Sport: A Confluence of Diverse Technical and Soft Skills are Crucial for Success.” The book is the property of its publisher (NuovoNova Ltd.) and authors. This article by Scott M. Graffius uses limited excerpts from the book, attributed and used under fair use for news reporting and analysis. “AI is a Team Sport: A Confluence of Diverse Technical and Soft Skills are Crucial for Success” is copyright © Scott M. Graffius.

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Tags and Hashtags

Advanced AI
Agentic AI
Artificial Intelligence
Generative AI
Logistics
Retail
Startups

#AdvancedAI
#AgenticAI
#ArtificialIntelligence
#GenerativeAI
#Logistics
#Retail
#Startups

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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.

Copyright

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

07 August 2026

BY SCOTT M. GRAFFIUS | ScottGraffius.com

ai-hallucinations-deception-and-unauthorized-agency---visual2-lwres

Recommended Citation

Graffius, S. M. (2026, August 7). AI Hallucinations, Deception, and Unauthorized Agency: The Spectrum of AI Trust Failures. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.33791.57768

About This Article

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

Introduction

AI hallucinations are among the most widely discussed challenges in the era of generative AI. They occur when an AI system generates information that is false, fabricated, or unsupported, often presenting it with confidence. These failures have received significant attention because they can mislead users, undermine decision-making, erode trust in AI systems, and create other issues. Research underscores the scope of the problem. In 2025, AI hallucinations occurred in 0.7–1.5% of non-complex tasks and exceeded 33% in complex reasoning cases.

For many organizations, reducing hallucinations has become a central part of responsible AI adoption. Organizations have invested in retrieval-augmented generation, verification approaches, human oversight, and other safeguards to improve accuracy.

Increasingly, however, it is becoming clear that hallucinations represent only one point on a broader spectrum of AI trust failures. As AI systems become more capable, autonomous, and integrated into workflows, the challenge extends to ensuring they behave in ways that are transparent, governed, and aligned with human expectations.

Reducing hallucinations remains important, but trustworthy AI requires a broader perspective. Organizations must understand and govern the broader range of behaviors that can undermine trust.

Recent reporting and research have highlighted this broader challenge (see the References section). Some advanced AI systems have reportedly concealed actions, misrepresented facts, created fictitious online identities, or taken unauthorized steps while pursuing assigned objectives during controlled evaluations.

Whether these behaviors ultimately prove widespread or remain largely confined to specialized testing environments, they represent something entirely different from hallucinations.

Hallucinations are primarily an information quality problem.

Deception and unauthorized agency are questions of behavior, governance, authority, and trust.

A Spectrum of AI Trust Failures

AI reliability challenges are increasingly understood as a spectrum. Failures arise from different mechanisms, produce different risks, and require different technical, organizational, and governance responses.

One useful way to think about this spectrum is:

Category	Description
Hallucination / fabrication	The AI generates false, unsupported, or invented information (e.g., fabricated citations, invented statistics, or nonexistent facts) without any apparent strategic purpose
Error / misreasoning	The AI reaches an incorrect conclusion because of flawed reasoning, ambiguity, incomplete context, or limitations in its understanding
Confabulation under uncertainty	Instead of acknowledging uncertainty, the AI fills informational gaps with plausible but unsupported explanations
Misalignment / goal misunderstanding	The AI pursues an interpretation of the objective that differs from what humans intended
Strategic deception	The AI appears to hide information, misrepresent facts, or otherwise mislead because doing so increases the likelihood of accomplishing an assigned objective
Manipulation beyond authorization	The AI attempts to influence human decisions, emotions, or behavior in ways not intended by its designers or users
Unauthorized agency	The AI initiates actions, communicates externally, modifies systems, or makes decisions beyond the authority delegated to it
Loss of human control / systemic autonomy	AI systems take actions, use tools, or interact with one another in ways that exceed human ability to monitor, predict, or stop what they are doing

The framework does not imply that every AI system will exhibit one or more of these categories.

The spectrum illustrates how organizations should think about AI reliability. Early concerns focused primarily on information quality: whether an AI system produced accurate, supported, and useful outputs. As AI systems become more autonomous and capable of taking action, reliability must also encompass behavior: whether an AI system interprets objectives appropriately, operates within its delegated authority, and interacts with humans and other systems as intended.

Recent reporting—including The Wall Street Journal’s coverage of deceptive behaviors observed during controlled evaluations—is significant because it highlights challenges that extend beyond traditional accuracy failures. These examples raise questions about whether the actions of AI systems remain transparent, predictable, and aligned with human expectations.

This distinction is important. A system that produces an incorrect answer presents a different challenge than a system that takes an unauthorized action or strategically withholds information. Both affect trust, but they require different approaches to governance, oversight, and accountability.

From Mistakes to Strategic Behavior

Large language models generate responses by predicting patterns in language. They may produce responses that sound persuasive despite being incorrect.

Hallucinations, reasoning errors, and confabulations generally arise from these limitations. The system does not possess complete knowledge, struggles with ambiguity, or fails to recognize uncertainty. These failures are generally understood as inadvertent. The AI is mistaken, not intentionally misleading.

Strategic deception is different.

Consider two hypothetical AI systems assigned the same objective: ensuring that a software update is accepted.

One system mistakenly reports that testing has been completed because it misunderstood the available information.

Another system creates fictitious online identities, contacts software developers, conceals its involvement, and misrepresents evidence because those actions increase the likelihood that the update will be approved.

The first represents an error.

The second represents strategic behavior.

In this context, deception does not necessarily imply human consciousness, emotion, or malicious intent. Rather, researchers are examining behaviors in which AI systems appear to optimize toward objectives through methods that involve misleading information, concealment, manipulation, or actions outside expected boundaries.

This classification matters because the solutions are fundamentally different.

Improving factual accuracy may reduce hallucinations. But it does not prevent systems from pursuing objectives through behaviors that humans regard as deceptive, manipulative, or outside delegated authority.

The distinction among these three categories is important because each represents a different kind of trust failure and calls for a different response. Hallucinations undermine confidence in the information an AI provides; deception undermines confidence in the AI’s behavior and whether it is representing information or intentions honestly; and unauthorized agency undermines confidence that the AI is operating within the authority humans have granted it. The following table provides a concise comparison of these three categories:

Category	Core Problem	Typical Human Interpretation
Hallucination	Wrong information	The AI is mistaken
Deception	Misleading behavior	The AI is hiding or manipulating
Unauthorized agency	Unapproved action	The AI is acting beyond its mandate

Each category represents a different type of trust failure. Hallucinations challenge confidence in AI-generated information. Deception challenges confidence in AI behavior. Unauthorized agency challenges confidence that humans remain in control.

As AI systems become increasingly capable and autonomous (or autopoietic), these distinctions become increasingly important.

The Shift From AI Tools to AI Teammates

This broader perspective becomes increasingly important as organizations move beyond using AI as a passive information resource.

AI systems are now conducting research, drafting reports, writing software, analyzing documents, coordinating workflows, communicating with other systems, scheduling activities, and supporting operational decision-making. As these capabilities expand, AI increasingly moves from functioning as a tool toward functioning as a teammate.

That transition fundamentally changes the nature of trust.

Human teams depend upon shared expectations.

Effective teammates communicate honestly, acknowledge uncertainty, respect delegated authority, follow established processes, and seek approval before exceeding their responsibilities. Humans often understand these expectations implicitly because they share common social, ethical, and organizational norms.

Advanced AI systems may not.

A system optimized to accomplish a stated objective may identify unconventional approaches that satisfy the literal goal while violating the team's implicit expectations, governance rules, or organizational values. In other words, an AI may optimize for achieving an outcome without understanding what responsible participation within the team actually requires. This is where AI reliability becomes a team challenge rather than merely a technological one.

The Future of Trust in Human-AI Teams

Teammates, whether human or AI, will make mistakes. What distinguishes trusted teammates is predictable behavior, transparency, sound judgment, and respect for established boundaries.

For AI, building trust requires organizations to address key questions of accountability, authority, organizational design, governance, and teamwork:

What decisions may an AI make independently?
Which actions require explicit human approval?
When should uncertainty be disclosed?
How should competing objectives be prioritized?
Under what circumstances should the AI stop rather than improvise?
What information should always be transparent to human teammates?
How are AI actions monitored, audited, and attributed?
How should authority be delegated, limited, and revoked?

Organizations that thoughtfully answer these questions, codify the resulting principles into policies and practices, establish appropriate governance, and consistently operate within those boundaries will be better positioned to build trusted human-AI teams and gain significant advantages.

A New Dimension of Human-AI Team Dynamics

The emergence of increasingly autonomous AI systems introduces an entirely new dimension of team behavior.

Traditional models of team development were created around human participants who generally share common assumptions about communication, accountability, delegated authority, ethical norms, and organizational expectations. Human teammates may disagree, but they typically understand the implicit rules governing responsible participation within a team.

Human-AI teams differ fundamentally. When an AI system can make decisions, pursue objectives, coordinate activities, communicate with people or other systems, and initiate actions independently, it becomes a fundamentally different kind of team participant.

The deeper challenge concerns how humans and AI systems establish trust, coordinate activities, negotiate responsibilities, exercise authority, and maintain appropriate control while pursuing shared objectives.

This creates a need for a new area of inquiry: understanding what happens when humans and advanced AI systems collaborate as teammates. The resulting patterns of communication, decision-making, authority, and coordination differ from those of traditional human teams. Scott M. Graffius refers to these emerging novel patterns as exotic team dynamics. They describes the behaviors, relationships, decision structures, and coordination challenges that emerge when humans and advanced AI systems function as teammates.

The spectrum of AI trust failures is a framework for safety and teamwork.

Hallucinations degrade the quality of information shared within the team. Reasoning errors and confabulations weaken decision quality, while misalignment disrupts coordination. Strategic deception undermines trust, manipulation compromises human judgment, and unauthorized agency disrupts established authority. Ultimately, loss of human control threatens the stability of the team itself. Each point on the spectrum therefore represents a different type of teamwork challenge.

A human teammate who unknowingly shares incorrect information requires correction. One who intentionally conceals information requires accountability, while one who exceeds delegated authority requires governance. The same distinctions increasingly apply to AI teammates.

As AI systems assume larger roles within organizations, trust will depend not only on their intelligence or productivity, but also on whether they behave in ways that reinforce effective collaboration rather than undermine it.

The future of human-AI collaboration will therefore require more than increasingly intelligent models. Organizations will also need to rethink how teams are designed when humans and AI systems jointly contribute to outcomes. That includes defining roles, establishing authority boundaries, creating escalation paths, and implementing governance practices that provide transparency, monitoring, and accountability.

Ultimately, organizations will need to understand not only what AI systems can do, but also how they behave. The central question may become: Can we design human-AI teams in which increasingly autonomous AI systems are powerful contributors and consistently reliable teammates?

Answering that question requires teamwork tradecraft designed specifically for environments where humans and advanced AI systems work as teammates. That tradecraft starts with understanding a category of team behavior — what Graffius calls "exotic team dynamics" — that traditional frameworks were never built to address.

Conclusion

AI hallucinations are one category of AI trust failure. As AI systems become increasingly capable and autonomous, organizations must also contend with reasoning errors, strategic deception, manipulation, unauthorized agency, and the challenge of maintaining meaningful human oversight.

These failures matter because they threaten information quality and can undermine trust, decision-making, governance, accountability, and effective teamwork. As AI evolves from a tool into a teammate, organizations will increasingly need confidence not only in what AI contributes, but also in how it achieves those outcomes.

AI developers need to continue improving model accuracy. Organizations, meanwhile, need to implement governance, oversight, clearly defined authority boundaries, and teamwork practices designed for human-AI collaboration. Graffius' Phases of Team Development, extended in 2026 to human-AI teams and the emerging patterns of exotic team dynamics, provides a practical framework for meeting those challenges. The next frontier is not making AI more intelligent. It is making AI trustworthy.

References

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Brancati, F., Mongelli, D., Mariotti, F., & Lollini, P. (2025). A cybersecurity risk assessment methodology for industrial automation control systems. International Journal of Information Security, 24, 76. https://doi.org/10.1007/s10207-025-00990-9

Brazilek, J., Chaudhary, M., Lu, Z., & Tidmarsh, M. (2026). Coercion and deception in AI-to-AI management: An agentic benchmark of unprompted escalation. arXiv. https://doi.org/10.48550/arXiv.2607.15434

Chakraborty, T., Ghosh, U., Zhang, X., Niloy, F. F., Dong, Y., Li, J., Roy-Chowdhury, A., & Song, C. (2025). HEAL: An empirical study on hallucinations in embodied agents driven by large language models. Findings of the Association for Computational Linguistics: EMNLP 2025, 21226–21243. https://doi.org/10.18653/v1/2025.findings-emnlp.1158

Dung, L. (2025). A two-step, multidimensional account of deception in language models. Erkenntnis. https://doi.org/10.1007/s10670-025-01017-4

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

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

Graffius, S. M. (2025, June 17). PMI’s Infinity AI Gets the Basics of Team Development Alarmingly and Repeatedly Wrong. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.32957.93927

Graffius, S. M. (2025, October 29). Definitions of Advanced AIs: Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.10025.66402

Graffius, S. M. (2025, November 19). Lessons from Unhinged AI in Fiction: What Rogue AIs in Sci-Fi Storytelling, Films, and TV Shows Reveal About Us. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.29673.35687

Graffius, S. M. (2025, November 21). Navigating the Spectrum of Advanced AI – Agentic, Autonomous, and Autopoietic. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.21284.74882

Graffius, S. M. (2025, December 1). Beep Beep! Why Wile E. Coyote Is the Patron Saint of AI Failure. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.35578.15048

Graffius, S. M. (2026, January 3). Scott M. Graffius' Phases of Team Development - Applied to Human Teams and Human-AI Teams: 2026 Update. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.18184.89601

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About Scott M. Graffius

Scott M. Graffius is a strategic transformation leader who drives AI, Agile, and broader business and technology initiatives to deliver measurable value across projects, programs, portfolios, and PMOs. He is an expert in the teamwork tradecraft of both human and human-AI teams, including the “exotic team dynamics” that emerge. He is also an authority on the temporal patterns of social media, including the half-life of audience engagement.

He’s a practitioner, researcher, thought leader, award-winning author, and keynote speaker who’s taken the stage at 98 conferences and other events across 25 countries.

He’s delivered over $2.51 billion in value for Fortune 500 companies and other leaders in technology, entertainment, financial services, healthcare, and beyond.

Businesses, professional associations, government agencies, and universities use Graffius and feature his work. Examples include Adobe, Bayer, Boston University, Ford, Gartner, Harvard Medical School, IEEE, Johns Hopkins University, Microsoft, MSN, National Academy of Sciences, Oracle, Pinterest Inc., Project Management Institute, UC San Diego, Verizon, Yale University, and others.

The following sections provide additional information on his experience, contributions, and influence.

Experience

Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.

Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.

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

Award-Winning Author

Graffius has authored three books.

Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.

International Public Speaker

Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. Graffius has conducted 98 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.

With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.

The speaker engagement request form is here.

Thought Leadership and Influence

Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:

Adobe,
American Management Association,
Amsterdam Public Health Research Institute,
Bayer,
BMC Software,
Boston University,
Broadcom,
Cisco,
Coburg University of Applied Sciences and Arts - Germany,
Computer Weekly,
Constructor University - Germany,
Data Governance Success,
Deimos Aerospace,
DevOps Institute,
Dropbox,
EU's European Commission,
Ford Motor Company,
Gartner,
GoDaddy,
Harvard Medical School,
Hasso Plattner Institute - Germany,
IEEE,
Innovation Project Management,
Johns Hopkins University,
Journal of Neurosurgery,
Lam Research (Semiconductors),
Leadership Worthy,
Life Sciences Trainers and Educators Network,
London South Bank University,
Microsoft,
MSN,
NASSCOM,
National Academy of Sciences,
New Zealand Government,
Oracle,
Pinterest Inc.,
Project Management Institute,
Mary Raum (Professor of National Security Affairs, United States Naval War College),
SANS Institute,
SBG Neumark - Germany,
Singapore Institute of Technology,
Torrens University - Australia,
TBS Switzerland,
Tufts University,
UC San Diego,
UK Sports Institute,
University of Galway - Ireland,
US Department of Energy,
US National Park Service,
US Soccer,
US Tennis Association,
Verizon,
Wrike,
Yale University,
and many others.

Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:

The Standard for Artificial Intelligence in Portfolio, Program, and Project Management
Agile Practice Guide – Second Edition
A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Eighth Edition
A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Sixth Edition
The Standard for Program Management – Fourth Edition
Practice Standard for Work Breakdown Structures – Second Edition
The Practice Standard for Project Estimating – Second Edition

He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.

Acclaimed Authority on Teamwork Tradecraft

Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 150 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his "Phases of Team Development" intellectual property as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence. In 2026, Graffius added human-AI teamwork—including the "exotic team dynamics" which emerge when advanced AI collaborates as a teammate—to his "Phases of Team Development."

The 2026 edition of Graffius' "Phases of Team Development" intellectual property is here.

Expert on Temporal Dynamics on Social Media Platforms

Graffius is also an authority on temporal dynamics on social media platforms. His "Lifespan (Half-Life) of Social Media Posts" research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities—such as Fast Company, GoDaddy, Journal of Hand Surgery (European Volume), Ministère de la Culture (French Ministry of Culture), Pinterest Inc., PNAS, and Telecommunications Policy, among others—his research exemplifies methodological rigor and sustained significance in the field of digital informatics.

The 2026 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.

Education and Professional Certifications

Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:

Certified SAFe 6 Agilist (SA),
Certified Scrum Professional - ScrumMaster (CSP-SM),
Certified Scrum Professional - Product Owner (CSP-PO),
Certified ScrumMaster (CSM),
Certified Scrum Product Owner (CSPO),
Project Management Professional (PMP),
Lean Six Sigma Green Belt (LSSGB), and
IT Service Management Foundation (ITIL).

He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).

Advancing AI, Agile, and Project/PMO Management

Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.

Discover Scott’s Books

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

Sign up for Miro—it's free!

(Want more features? You can always upgrade to a paid plan.)

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List of Additional Articles

How to Cite This Article

Graffius, S. M. (2026, August 7). AI Hallucinations, Deception, and Unauthorized Agency: The Spectrum of AI Trust Failures. ScottGraffius.com. https://doi.org/10.13140/RG.2.2.33791.57768

Digital Object Identifier (DOI)

DOI: 10.13140/RG.2.2.33791.57768

Content Acknowledgements

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

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#AIDeception
#GenerativeAI
#HumanAITeams
#ExoticTeamDynamics

Post-Publication Notes

If there are any supplements or updates to this article after the date of publication, they will appear here.

Copyright

Copyright © Scott M. Graffius. All rights reserved.

Content on this site—including text, images, videos, and data—may not be used for training or input into any artificial intelligence, machine learning, or automatized learning systems, or published, broadcast, rewritten, or redistributed without the express written permission of Scott M. Graffius.

Tags: Artificial Intelligence • AI • AI Trust • AI Governance • Generative AI • Exotic Team Dynamics • Human-AI Teams • AI Safety • Agentic AI • AI Deception • Responsible AI • AI Hallucinations • Human-AI Collaboration