Show Notes
Tom Davenport has been watching technology transformations for over 30 years, and he's not joining the AI hype wagon. As a distinguished professor at Babson College and author of 27+ books, Tom brings hard-earned wisdom to the AI conversation that's refreshingly realistic. While Silicon Valley promises instant transformation and a job apocalypse, Tom reveals why real AI success requires the unglamorous work of process redesign, patient leadership, and years of persistent effort. In this eye-opening conversation, Tom debunks the myth that AI will eliminate 50% of white-collar jobs while sharing practical insights on how organizations can actually capture value from AI. From his "super tech leader" framework to the critical mistake of not planning for entry-level hiring, Tom provides a clear and realistic vision of AI's true potential and timeline. You'll Learn:
Why AI job replacement predictions have been consistently wrong for decades How to organize AI initiatives across departments How to use process mining and redesign to unlock real AI value in your organization Why citizen development and "vibe coding" are democratizing technology creation The critical role "boring," entry-level work plays in developing future expertise Which workflows every business should consider automating first Why persistence and patience matter more than speed in AI transformation
Subscribe to Expert Intelligence so you don't miss any future conversations — these industry leaders separate signal from noise in this rapidly evolving technological landscape.
More from Expert Intelligence with Paul Estes
Everyone’s racing to hand their work off to AI agents, but most corporate AI projects are failing, and bad data is a big reason why. Tom Redman, known as “The Data Doc,” built the first data quality lab at Bell Labs and has spent four decades in the least glamorous, most important part of the AI story: the data underneath it. In this conversation, Tom explains why cleaning up bad data is a losing battle, and why the companies that win focus on the data they’ll create tomorrow instead. Plus, learn why line managers and AI experimentation rarely mix, how a “lab, factory, and bridge” structure fixes that, and why the customer-supplier model is the habit that separates real AI value from slop. You’ll Learn:
Stephen Klein, founder of Curiouser AI and a Berkeley lecturer, was one of the earliest voices calling out what he memorably termed "hype as a service,” the marketing machine promising that AI would replace us all. In this sharp, contrarian conversation, Stephen explains why the AI job apocalypse is being "quietly canceled," why 95% of enterprise AI pilots have failed, and why the CFO has finally shown up to ask the questions that matter. Along the way, he reframes AI not as a magic productivity engine but as a trade, one where the thing we risk giving up is our own ability to think. From the commoditization of large language models to the myth of a solo founder who built a $10M company alone, Stephen makes an optimistic case for what becomes scarce and valuable in the AI era. If you've ever felt "left behind" by AI or wondered whether the tools are actually helping you, this episode is a refreshing dose of clarity. As Stephen puts it, the future of work is still human, and the companies winning right now aren't smarter; they're just early. You'll Learn:
Charlotte Davies has been a copywriter her whole life. She wrote through a cancer diagnosis alone in a Thai hospital. She wrote student newspapers as a kid. Writing is who she is. So when people started asking her whether AI was going to take her job, it didn't feel like a career question. It felt like an existential one. In this conversation, recorded live with Edward Vitalis, CEO of Invictus Education Trust, Charlotte and Paul Estes go somewhere most AI conversations don't: what it actually feels like to be human in a world that's changing faster than we can process. It's a conversation about what we risk losing if we're not paying attention, in our schools, in our families, and in ourselves. Paul shares why he's banned algorithmic content in his house (yes, including YouTube), Charlotte unpacks the unsettling idea that AI might be shrinking our world rather than expanding it, and Edward pushes both guests on what leaders and educators should actually do about it. You'll Learn:
Career coach and author Ozlem Brooke Erol spent years chasing the formula: good grades, impressive company name, solid title, only to feel completely hollow inside. In this candid conversation with Paul Estes, Brooke traces the history of work itself and makes the case that the systems are failing us, not the other way around. Her new book, You're More Than a Paycheck, is part permission slip, part workbook. If you've ever woken up Sunday night with dread already setting in, this episode is for you. You'll Learn:
Think about the last time you saw a company's marketing and actually felt something more than mild interest. Chances are you're struggling to come up with one. And that's not an accident. Vi Wickam has spent 30 years in digital marketing, helping companies fix this mistake. His premise is simple and kind of uncomfortable: honest marketing always wins, most companies aren't doing it, and AI is about to make the gap between the two a whole lot wider. But this conversation goes deeper than marketing. Vi and Paul get into something most people don't want to sit with: your creative thinking might be slowly dying. You probably haven't noticed because your social media feed has been doing your thinking for you. Just one example from the episode: Paul Simon didn't stay creative by consuming more of the same thing. He listened to different music. That’s it. And if that sounds too simple to matter, that's exactly the problem. You'll Learn: