#206: Building AI Councils That Work, Motivating Passive Adopters, Why Pilots Stall, and Amazon’s AI Slowdown
Episode Description
Not a single company leader Paul has spoken with is fully prepared for what AI is about to do to their workforce. In this AI Answers episode, Paul and Cathy work through 15 real questions from a recent Scaling AI class, covering everything from the AI divide inside companies to why most AI strategies fail before they start.
Topics include job displacement and underemployment, why enterprises handed AI to IT and get stuck, the automation-vs-augmentation spectrum by seniority level, what knowledge work looks like in three years, and why showing a skeptical CEO results beats showing them prompts every time.
00:00:00 — Intro
00:06:09 — Is Amazon slowing its AI rollout a sign of maturity?
00:08:58 — Are large enterprises structurally disadvantaged in the AI era?
00:12:14 — Who owns the AI adoption and data readiness problem?
00:14:56 — Is there a growing AI divide between power users and everyone else?
00:21:16 — What AI take do most people disagree with?
00:22:47 — Can companies automate too much too fast?
00:26:19 — Does automation eventually take over or do we land in the middle?
00:28:24 — What does the average knowledge worker's job look like in three years?
00:35:02 — What are companies still getting wrong about AI strategy?
00:36:27 — How should leaders should decide what matters versus what’s noise?
00:40:21 — What separates AI councils that drive progress from ones that don't?
00:41:47 — Where is governance necessary and where does it get in the way?
00:45:17 — Should you show leadership the AI system or the results?
00:47:19 — What's the no-brainer AI use case most companies still haven't tried?
00:49:36 — Why do people wait to be told how to use AI instead of experimenting?
Show Notes: Access the show notes and show links here
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