Before leaders can redesign their organizations with AI, they have to reconsider how they personally think, work, and make decisions.

In this special episode of Unlearn, Barry O’Reilly shares the opening chapter of the audiobook edition of Artificial Organizations, narrated in his own voice. After hearing from readers who wanted another way to experience the book, Barry spent four days in the studio bringing its ideas and stories to life. The process was rewarding, demanding, and personal. As someone who is dyslexic, reading every word aloud required a different kind of focus from delivering a keynote, teaching a workshop, or hosting a podcast conversation.

Barry then takes listeners into the central argument of the book: organizations often begin AI adoption with licenses, pilots, and tools while leaving leadership behavior and decision-making systems unchanged. Drawing from his own experiments, leadership research, and work with senior teams across North America, Europe, and Asia, he explains why meaningful AI transformation starts with human traits, high-value tasks, and the judgment leaders must preserve before selecting technology.

Key Takeaways

AI should strengthen judgment, not simply increase output: Machines can process and synthesize information at a scale no individual can match, but leaders still have to decide what matters. The opportunity is to use AI to prepare, capture, and pressure-test thinking so human attention stays focused on consequential decisions.
Start with traits, then tasks, then tools: Barry’s 3T model begins with how a leader naturally thinks, creates, communicates, and decides. Only after identifying the tasks where that judgment creates the most value should leaders choose tools to support the work.
Decision velocity must be paired with decision advantage: Decision velocity is how quickly a leader moves from question to insight, decision, and action. Decision advantage is the quality and depth of context behind that choice; speed without insight creates chaos, while insight without timely action becomes irrelevant.
Most leadership time is allocated away from leadership value: Barry describes an 80/20 mismatch in which meetings, updates, administration, and context reconstruction consume most of a leader’s time, while the greatest value comes from framing problems, evaluating tradeoffs, and making high-stakes decisions.
Organizational AI adoption begins with personal behavior change: Broad mandates, task forces, and tool rollouts are often the wrong starting point. Leaders build more credible adoption when they experiment in their own workflows, share what they learn, and make new behaviors visible to their teams.

Additional Insights

Presence can be more valuable than productivity: Barry’s first AI experiment used a meeting assistant to capture and synthesize conversations. The practical gain was not only faster preparation and follow-up; it allowed him to stop carrying every detail in his head and remain fully present during critical discussions.
Experience becomes a liability when it is not augmented: The instincts and institutional knowledge that helped leaders succeed can become limiting when they are treated as sufficient. Experience keeps compounding only when leaders combine it with broader recall, faster synthesis, and continuous testing.
Senior leaders need psychological safety to learn: Barry’s executive study found that leaders preferred one-on-one coaching and small peer cohorts over large workshops or self-paced courses. Being a beginner is uncomfortable at senior levels, so smaller environments make experimentation and honest questions easier.
New capacity should create thinking space, not more workload: In the Progeny case study, AI reduced the effort required to capture meetings, actions, owners, and deadlines. CEO Peter Nevsky framed the resulting capacity as time for strategic thought and better decisions rather than an invitation to place people on a faster operational treadmill.
The unit of change is the judgment inside a role: AI may automate parts of a project manager’s, analyst’s, or executive’s work while increasing the importance of interpretation, challenge, and decision quality. The role may remain, but the judgment required within it changes.

Episode Highlights

00:00 – Episode Introduction & Why I Created the Audiobook

Barry introduces this special preview of the Artificial Organizations audiobook, shares why he chose to narrate it himself, and explains why leaders need a different approach to AI adoption through the 3T framework: Traits, Tasks, and Tools.

04:33 – A Quick Favor Before We Begin

Barry invites listeners to leave an Amazon review, recommend the audiobook to their network, and help more leaders discover its ideas.

05:16 – Preface: Why the Way We Work Is Broken

Barry introduces the central challenge facing modern organizations: leaders are overwhelmed by information, while better decisions remain harder than ever.

07:11 – Judgment Under Pressure

Barry explores why more data, more tools, and more technology haven't created better leadership, arguing that the real constraint is our ability to process information and make sound judgments.

10:07 – The First AI Leadership Experiment

A simple experiment with an AI meeting assistant transformed Barry's leadership by improving clarity, presence, and decision-making, leading to a new perspective on AI's role.

12:00 – AI as Judgment Infrastructure

Barry reframes AI as more than a productivity tool, explaining how it strengthens judgment, improves decisions, and helps leaders focus on what matters most.

16:07 – Part One: The Judgment Constraint

Barry introduces the first section of the book, explaining why AI creates little value unless it changes how leaders think, decide, and lead.

18:08 – Chapter One: Your Legacy Is Now Your Liability

Barry examines why experience alone is no longer enough and how decision velocity and continuous learning are becoming the defining advantages of modern leadership.

22:20 – The AI ROI Blind Spot

Barry challenges the common focus on efficiency and cost reduction, arguing that AI's greatest value lies in helping leaders make better and faster decisions.

28:16 – From Linear Leadership to Exponential Innovation

Barry explains why traditional leadership models struggle in the AI era and why organizations must adopt new ways of learning, experimenting, and making decisions.

34:10 – What Makes an Artificial Organization

Barry defines artificial organizations and shares how leaders can replace memory-based management with shared judgment systems that accelerate decision-making and collaboration.

40:09 – The New Leadership Divide

Barry explores the widening gap between leaders who actively experiment with AI and those who continue relying on legacy ways of working, and why that difference will compound over time.

43:15 – Where to Start

Barry explains why successful AI transformation begins with personal experimentation, encouraging leaders to model new behaviors before scaling change across their organizations.

45:15 – Closing Reflections

Barry concludes the first chapter, thanks listeners for joining this special audiobook preview, and invites them to continue the journey with Artificial Organizations.

FAQs

Q1. Is this Unlearn episode an audiobook preview?

Yes. This special episode includes Barry O’Reilly’s recorded introduction followed by the opening chapter of the audiobook edition of Artificial Organizations, narrated by Barry himself. He explains why the audio edition was created, what recording the book required, and how its ideas connect to his work with executive leaders and teams.

Q2. What is an artificial organization?

An artificial organization is a company that deliberately combines human and machine intelligence to redesign how context is captured, information is synthesized, and decisions are made. Instead of adding AI to the edges of existing workflows, it builds judgment infrastructure into how the organization operates.

Q3. How can leaders use AI to make better decisions?

Leaders can use AI to capture conversations, summarize context, test assumptions, explore scenarios, prepare for meetings, and identify unresolved actions. This reduces the information leaders must carry mentally and gives them more capacity to focus on tradeoffs, consequences, and high-value judgment.

Q4. What is the difference between decision velocity and decision advantage?

Decision velocity is the speed at which a leader moves from a question to insight, decision, and action. Decision advantage is the quality, accuracy, and depth of context behind that decision. Strong leadership requires both because speed without insight creates chaos, while insight without action loses relevance.

Q5. Why do many enterprise AI initiatives fail to create business value?

They often begin with tool purchases, pilots, and mandates without redesigning how work, context, and judgment flow through the or...