On this episode of The Data Storytellers Podcast, Rich Heimann, author of Doing AI, GenAI Revealed, and the newly released Sutskever's List, joins us for a deep and provocative conversation on why most enterprise AI initiatives fail.

Rich unpacks how internal power structures, belief systems, and corporate incentives shape what AI gets funded, how it's framed, and why so many efforts fall short. We explore the gap between organizational theater and technical progress, and why understanding human systems matters more than mastering the technical stack.

If you're an AI or data leader struggling with implementation, this episode offers a fresh lens that might explain why the problem isn't your model.

Want more? Rich’s new book Sutskever’s List: Foundational Ideas of Modern AI is now available — and you can get it HERE with 45% off.

Chapters:

00:00 – Introductions and Rich’s background
02:44 – The real reasons AI adoption fails in enterprise settings
07:12 – Power, status, and the illusion of AI progress
12:25 – Why many AI initiatives are more about performance than impact
17:31 – Data science vs business theater: who’s really calling the shots?
21:50 – Cultural friction: how belief systems shape technical outcomes
26:43 – Rich on the danger of over-rationalizing human systems
32:17 – Lessons from behavioral economics and AI ethics
37:09 – What leaders pretend to want vs what they actually support
42:03 – Redefining AI success: who gets to decide what matters?
47:58 – Stories vs truth: how narratives become strategy
53:11 – The objectivity myth and why some orgs cling to it
59:04 – LLMs, RAGs, and the current moment of hype
1:04:50 – Why technologists need to understand organizational design
1:09:44 – Advice for AI leaders trying to make change stick
1:14:02 – Final reflections on trust, transformation, and learning