AI projects succeed when teams define success from the start. Cassie Kozyrkov discusses how clear metrics guide risk, reduce rework, and ensure systems perform in real-world workflows.
CEO, Google's first Chief Decision Scientist, AI Adviser, Decision Strategist, Keynote Speaker (makecassietalk.com), LinkedIn Top Voice
Leaders are discovering the hard way that “plug-and-play AI” is mostly a myth. The tech may look polished, but the real work begins where the glossy demo ends. This new episode of AI in Action breaks down why so many teams burn budget, time, and momentum before they ever see meaningful value — and why the missing ingredient is almost always the same: precise, upfront definitions of success. ❌ Clear metrics aren’t paperwork. ✅ They’re strategic infrastructure. Without them, AI initiatives drift, stall, or quietly accumulate hidden costs. With them, teams avoid rework, manage risk, and actually ship systems that hold up under the pressure of real users and real workflows. If you’ve ever watched an AI project spiral because “it looked easy at first,” this one will resonate. We also dig in to an irreconcilable conflict between you and your vendor. 🎥 Video below. Your turn: What’s one “plug-and-play” promise you’ve seen turn into a long, messy integration story? Your comments make the (digital) world go around and your reposts ♻️ make my day. #AILeadership #DecisionIntelligence #GenerativeAI #AIinAction #Strategy #DigitalTransformation Don't forget to mash, ahem no, daintily tap that follow button for more.
