AI hype is everywhere—but most projects still flop because the data underneath is messy, siloed, and ungoverned. In this episode, we unpack why 85% of AI and ML initiatives fail, how the “hidden data factory” wastes billions of work hours, and what it really takes to make AI reliable: rigorous data hygiene, governance, and process change. From product and customer master cleanups to structured transaction histories and ongoing data stewardship, learn the pragmatic roadmap that turns AI from slideware into revenue.