Paul Gibbons
Most organisations are better at deploying AI than at using it. The workflows, decision habits, and cultural defaults of the existing organisation stay intact long after the new tools arrive. That gap between technical implementation and behavioral adoption is where most transformation investment is quietly lost.
The gap between deploying AI and actually using it is a behavioral problem, and Paul Gibbons, creator of the Adaptive Adoption framework and author of eight books on organizational change, helps C-suite leaders close it.
Full Profile
Why organisations work with Paul Gibbons
- His Adaptive Adoption model – a seven-pillar behavioral science framework for AI adoption – and its companion diagnostic, the Adaptive Adoption Maturity Index (AAMI), give leaders a structured tool for assessing and addressing the human conditions that determine whether an AI investment delivers returns or stalls. This kind of named, built IP is rare in this topic area.
- “The Science of Organizational Change” is cited by Google’s change team and Microsoft’s internal culture group as having reoriented how they approach transformation: an unusual form of verification that the intellectual framework holds up under real operational pressure, not just in consulting engagements.
- He will tell an organisation what is wrong with its change thinking. The Chairman of KPMG described the experience as hearing “what we needed to hear, not what we wanted to hear”, a quality that becomes valuable when senior leaders have quietly invested in approaches that are not working.
- His practitioner career spans founding one of Europe’s leading leadership consulting firms (Future Considerations), serving as Partner at IBM Consulting, and developing change management methodology in PwC’s Strategy, Innovation and Change practice, meaning the frameworks have been stress-tested in exactly the large, complex organisations that attend senior leadership events.
- His academic breadth spanning neurochemistry, economics, neuroscience, philosophy, and behavioral science – allows him to draw on disciplines rarely applied to organizational transformation, and to name and debunk the pseudoscience that fills a field where, as Stanford’s Jeffrey Pfeffer has noted publicly, charlatanism is common.
Biography highlights
- Founder and CEO of Future Considerations (2001), one of Europe’s leading leadership and culture change consulting firms, with named clients including Shell, BP, HSBC, Barclays, and KPMG
- Former Partner at IBM Consulting (Talent and Transformation); former senior strategist at PwC’s Strategy, Innovation and Change practice, where he developed its change management and corporate transformation methodologies
- Author of eight books including “The Science of Organizational Change” – named among the top change management texts of all time – and “Adopting AI: The People-First Approach” (2025)
- Ranked #5 globally in organizational culture change by Global Gurus; named among the top 52 globally in AI in 2026 (London Speaker Bureau)
- Fellow of the Royal Society of Arts (FRSA); Adjunct Professor of Business Ethics at the University of Denver (2015-2018); member of the American Philosophical Association and the U.S. Academy of Management Council
- Writing featured in The Wall Street Journal, The Financial Times, and The Guardian; endorsed by Jeffrey Pfeffer (Stanford Business School) and Simon Collins (Chairman, KPMG)
Biography
Most organisations know their AI and transformation investments are underperforming. The harder question is why and the honest answer, in most cases, is that the behavioural and cultural architecture of the organisation was never redesigned alongside the technology. Paul Gibbons has spent three decades building the evidence base that explains this failure, and the frameworks that help leaders act on it.
His intellectual contribution begins with a provocation. In “The Science of Organizational Change,” Gibbons argues that most change management frameworks are built on myth and untested pop psychology, and replaces them with approaches grounded in behavioural economics, neuroscience, and complexity theory. Google’s change team and Microsoft’s internal culture group both credited the book with reorienting how they approach transformation. Jeffrey Pfeffer of Stanford Business School praised his work for bringing scientific rigour to what he described as a field riddled with pseudoscience.
That critique evolved into a constructive framework for the AI era. His Adaptive Adoption model, a seven-pillar approach grounded in behavioral science, offers leaders a structured alternative to applying conventional change management to AI transformation. Its companion diagnostic, the Adaptive Adoption Maturity Index, helps organisations assess where they actually stand. The model draws on three decades of board and C-suite advisory work, including founding Future Considerations, one of Europe’s leading leadership consulting firms, serving as Partner at IBM Consulting, and developing change methodology in PwC’s Strategy, Innovation and Change practice.
Gibbons is a Fellow of the Royal Society of Arts and is ranked among the top five globally in organizational culture change by Global Gurus, and among the top 52 globally in AI in 2026. He has taught business ethics and leadership at the University of Denver, serves on the board of Denver’s Institute for Enterprise Ethics, and hosts the Think Bigger Think Better podcast, which explores the intersection of AI, behavioral science, and organizational leadership.
Key speaking topics
- Behavioral science and organizational change
- AI adoption and workforce transformation
- Culture change and behavior design
- Change management myths and evidence-based practice
- AI ethics and organizational governance
- Leadership in complex and uncertain environments
- The future of work and human-machine collaboration
Ideal for
- CHROs and people transformation leaders navigating technology-driven organizational change
- Boards and C-suite leaders making AI adoption and governance decisions
- Organizational development and change management practitioners
- Digital and technology transformation leaders in large, complex organizations
Audience outcomes
- A clear framework for understanding why culture change and AI adoption efforts typically fail, grounded in behavioral science rather than convention
- Practical tools for diagnosing where behavioral and cultural gaps are undermining technology investments
- A more rigorous basis for evaluating AI adoption strategies and distinguishing credible signals from market noise
- Language and framing for board and C-suite conversations about the organizational conditions required for successful transformation
- Familiarity with the Adaptive Adoption framework and Adaptive Adoption Maturity Index as structured, evidence-based alternatives to conventional change management applied to AI
Talks
This talk challenges conventional culture change efforts and shows how organisations can shift from abstract values to observable behaviors by redesigning context rather than mindset.
Key takeaways:
- Why culture conversations regularly fail to change behavior or outcomes
- How behavioral science explains the intention-to-action gap inside organisations
- Practical tools for designing environments that make new behaviors easier and more likely
This talk explores how AI can act as a capability multiplier across the existing workforce rather than a replacement for it.
Key takeaways:
- How AI can surface untapped potential across all levels of the organisation, not only at the top
- The business case for retaining and upskilling existing talent rather than hiring for scarce AI capability
- How to create the conditions where employees can experiment and build with AI safely
This talk helps leaders move beyond AI hype and make grounded strategic decisions in noisy, uncertain markets.
Key takeaways:
- How to distinguish meaningful AI signals from market noise and vendor claims
- Frameworks for evaluating the real business value of AI initiatives before committing resources
- Strategic approaches for deciding when to pause, pivot, or accelerate AI investments
This talk focuses on how behavioral science and people-first AI can remove workflow friction and make organisations work more effectively, not just faster.
Key takeaways:
- How to identify the human bottlenecks that slow down AI-enabled work in practice
- How to design workflows people actually follow, not just those documented in process maps
- Why the manager’s role shifts from supervising people to designing effective systems
This talk reframes workplace wellbeing through the lens of behavioral design and emerging AI-enabled tools.
Key takeaways:
- Why traditional corporate wellness programs fall short in high-pressure transformation environments
- How AI-enabled tools can support cognitive load management and recovery
- How behavioral design can embed sustainable performance into everyday workflows