In Practice: AI in the Enterprise | Day 30: 30 Days In: What We’ve Learned About the Gap Between AI Capability and AI Governance May 6, 2026
In Practice: AI in the Enterprise | Day 29: The Adoption Metric That Actually Predicts Success (It’s Not Usage) May 5, 2026
In Practice: AI in the Enterprise | Day 28: The Sunk Cost Fallacy in AI (Why Teams Keep Funding Programs That Should Die) May 4, 2026
In Practice: AI in the Enterprise | Day 27: The Org Structure That Actually Enables AI Governance (Hint: It’s Boring) May 1, 2026
In Practice: AI in the Enterprise | Day 26: What “Responsible AI” Actually Means in Production (Spoiler: It’s Boring and Unglamorous) April 30, 2026
In Practice: AI in the Enterprise | Day 25: How to Talk to Your Foundation Model Vendor About Risk (When They’re Not Used to Being Asked) April 29, 2026
In Practice: AI in the Enterprise | Day 24: The IP Risk You May Be Building Into Your AI System April 28, 2026
In Practice: AI in the Enterprise | Day 23: When AI Breaks Your Workflow (Not Because It’s Bad, But Because You Never Designed for Failure) April 27, 2026
In Practice: AI in the Enterprise | Day 22: The Dashboard Your Board Should Be Looking At (Hint: It’s Not What You’re Showing Them) April 24, 2026
In Practice: AI in the Enterprise | Day 21: You Can’t Have AI Governance Without Data Governance April 23, 2026
CodeDebate by Ben 