Paul Gibbons
Most organisations are better at deploying AI than at using it. The workflows and decision habits of the existing organisation stay intact long after the new tools arrive. That gap between technical implementation and behavioural adoption is where most transformation investment is quietly lost.
Paul Gibbons helps C-suite leaders close the gap between deploying AI and actually using it, drawing on his Adaptive Adoption framework and ten books on organisational change and behavioural science.
Full Profile
Why organisations work with Paul Gibbons
- The Adaptive Adoption framework gives leaders seven pillars for AI adoption grounded in behavioural science, and the Adaptive Adoption Maturity Model shows where an organisation actually stands against them. Both are published openly, so a buyer can inspect the method before booking.
- “The Science of Organizational Change” is cited by Google’s change team and Microsoft’s internal culture group as foundational to how they approach transformation, more than a decade after publication.
- Simon Collins, Chairman of KPMG, said Gibbons told them what they needed to hear rather than what they wanted to hear. He is direct with senior teams about where their change thinking is wrong.
- He founded Future Considerations, named Best Leadership Boutique by Leadership Excellence Magazine, served as a Partner in IBM Consulting’s Talent and Transformation practice, and developed the change methodology at PwC’s Strategy, Innovation and Change think-tank. Clients across that career include Shell, BP, Barclays, HSBC, Comcast and KPMG.
- His degrees are in biochemistry, organisational behaviour and philosophy, with postgraduate work in economics and neuroscience. He uses that range to name and dismantle the pseudoscience in change management, which is the argument of “Change Myths”, written with Tricia Kennedy.
Biography highlights
- Founder of Future Considerations (2001), named Best Leadership Boutique by Leadership Excellence Magazine, with clients including Shell, BP, HSBC, Barclays and KPMG
- Partner at IBM Consulting (Talent and Transformation); developed the change management and corporate transformation methodologies at PwC’s Strategy, Innovation and Change think-tank
- Author of ten books, including “The Science of Organizational Change”, ranked among the top change management texts of all time, “Adopting AI: The People-First Approach” (2025), and “Polymath Poker” (2026)
- Creator of Adaptive Adoption, the AI Leadership Delta and Behavioural Governance, with the Adaptive Adoption Maturity Model and AI Workforce Readiness Assessment published openly alongside seven research whitepapers
- 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
- Speaking at the Harvard Business School European Alumni Summit in Amsterdam, September 2026; previously at Talks at Google and the Microsoft Distinguished Author Program
Biography
Most boards now know their AI investments are underperforming. The harder question is why. In most organisations the behavioural and cultural architecture was never redesigned alongside the technology, and Paul Gibbons has spent three decades building the evidence base that explains it.
“The Science of Organizational Change” argued in 2015 that most change management frameworks rest on myth and untested pop psychology. It replaced them with behavioural economics, neuroscience and complexity theory. Google’s change team and Microsoft’s internal culture group both credit the book with reorienting how they approach transformation. Jeffrey Pfeffer of Stanford Business School calls him one of the most original thinkers in the change field.
That critique became a framework for the AI era. Adaptive Adoption sets out seven pillars for AI adoption built on behavioural science, with Change Agility, the AI Leadership Delta and Behavioural Governance as its three working components. Gibbons publishes the whole thing openly, with whitepapers, diagnostics and model cards free to download and argue with.
Those frameworks come out of board and C-suite work at scale. He founded Future Considerations, was a Partner in IBM Consulting’s Talent and Transformation practice, and built the change methodology at PwC. He now runs Paul Gibbons Advisory, coaching senior executives on AI over ninety-day sprints, and speaks at the Harvard Business School European Alumni Summit in Amsterdam in September 2026.
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 whose AI rollouts have stalled at pilot stage
- Boards and C-suite leaders making AI adoption and governance decisions
- Chief AI Officers and digital transformation leads in large, complex organisations
- Change management and organisational development practitioners
Audience outcomes
- Why AI and culture change programmes stall, explained through behavioural evidence instead of change management convention
- A measure of adoption based on what people demonstrably do with AI at work
- The seven pillars of Adaptive Adoption, and a read on where their own organisation sits against each using the Adaptive Adoption Maturity Model
- Language for board conversations about AI leadership capability, using the seven dimensions of the AI Leadership Delta
- A working view on which AI claims hold up and which are vendor noise
Talks
On what AI is doing to human cognition, and the skills question leaders are quietly worried about.
Key takeaways:
- What the research on cognitive offloading actually shows
- Why some workers report two to three times productivity gains while the evidence points the other way
- What leaders should do about skills development when both readings are true
On why individual AI gains of three to five times are not reaching the enterprise.
Key takeaways:
- A four-box friction model: load-bearing, theatre, ritual and turf-defending friction
- Which three types of friction do not earn their keep
- The leadership courage required to cut them
On building the support function most leaders cannot afford to hire.
Key takeaways:
- What a chief of staff role actually consists of, task by task
- How to assemble an always-available equivalent in a few hours
- Where the approach holds up and where it fails
On decision-making with incomplete information, drawn from Gibbons’ poker career and his 2026 book “Polymath Poker”.
Key takeaways:
- Expected value, Bayesian updating and range thinking as management tools
- How executives systematically misprice risk
- Why a good outcome and a good decision are different things
On the coming public reaction to AI and what it means for companies deploying it.
Key takeaways:
- Where the backlash is forming across trust, work, meaning and institutions
- What it means for organisations mid-deployment
- How to lead through it without retreating from the technology
On why Kotter and Prosci cannot carry AI adoption, and what replaces them.
Key takeaways:
- Why models built for go-live dates and stable end-states break on AI
- Change Agility as the capability to adapt continuously
- The leadership behaviours that build it