Why it feels like you're falling behind on AI - Barry O'Reilly (Author)

Barry O’Reilly is an entrepreneur, author, and founder of Nobody Studios, an early-stage venture studio focused on building AI companies. Over the last six years he has worked with founders, executives and enterprise leadership teams to rethink how organisations operate in the age of generative AI, while simultaneously building and launching companies inside the studio model.

A former startup advisor and executive coach, Barry has spent the last several years studying why most AI transformations fail despite enormous investment. Through his coaching and advisory work with leaders from companies including American Airlines, Skyscanner, and Slack, Barry has developed practical frameworks for improving decision-making, reducing administrative overhead, and increasing what he calls "decision velocity".

In this episode, Barry explains why AI adoption fails when companies focus on tools instead of behaviour change, why judgment is becoming the most important human skill, and how teams can use AI to improve collaboration rather than replace people.

Key takeaways
 — Most AI transformations fail because organisations start with tools instead of behaviours. Installing AI software does not change how people work, make decisions or collaborate.
 — The most effective AI use cases amplify a person’s natural way of working. Barry realised he produced better writing by talking through ideas and using transcription tools instead of forcing himself into traditional writing workflows.
 — Capturing meetings, conversations and decisions as structured data creates long-term organisational intelligence. Every interaction becomes a reusable asset that improves preparation, follow-through, and future decision-making.
 — Leaders must role-model AI adoption themselves. Organisations see better outcomes when executives openly experiment with tools, share lessons learned, and create psychological safety around adoption.
 — Decision velocity matters more than raw productivity. Teams improve when they arrive prepared, make decisions faster, reduce reversals, and spend more time solving meaningful problems instead of handling administration.
 — AI should be used to challenge thinking, not replace it. The most valuable prompts ask for blind spots, alternative scenarios, and pressure tests rather than definitive answers.
 — Teams working with AI outperform individuals working with AI. Barry cites research showing that collaborative ideation with AI produces significantly stronger outcomes than isolated use.
 — Productivity gains are meaningless if they simply create more exhaustion. The real opportunity is creating space for reflection, slow thinking, and better judgment.
 — Judgment is the critical human capability organisations cannot outsource. If people stop exercising judgment and rely entirely on AI-generated answers, they gradually erode their ability to make decisions under uncertainty.

Chapters
 1:03 — Building AI companies at Nobody Studios
 3:16 — Why AI transformations fail
 5:05 — The danger of focusing on tools
 6:35 — Discovering natural workflows with AI
 8:51 — Turning conversations into data assets
 12:02 — Measuring successful AI adoption
 13:14 — Why leaders must role-model behaviour change
 18:39 — Decision velocity as a leadership metric
 21:33 — Escaping administrative overload
 23:02 — Why leaders need time to think
 26:54 — What CFOs are worried about
 28:08 — Can AI replace startup teams?
 29:45 — Why distribution still matters most
 33:13 — Capturing and synthesising ideas with AI
 34:38 — Using AI to challenge your thinking
 37:11 — Avoiding top-down AI-driven strategy
 39:00 — Why teams plus AI outperform individuals
 42:31 — The problem with AI-generated certainty
 43:12 — Preserving human judgment
 44:55 — Hiring for judgment and decision-making
 47:19 — Final reflections on leadership and AI