Not every AI initiative succeeds—and the most valuable insights often come from what didn’t work. In this practitioner‑led session, four organizations share unfiltered case studies on where industrial AI deployments break down and why promising initiatives stall before reaching scale. Speakers will examine failed pilots, data readiness gaps and integration debt, organizational resistance, and change fatigue—along with the hard lessons learned along the way. Expect candid reflections on what teams would do differently if starting again, and practical guidance to help attendees avoid repeating the same mistakes in their own AI journeys.