Most enterprise AI initiatives don’t fail at the idea stage; they fail during implementation. In this session, I’ll share 5 key lessons from real-world AI adoption inside organizations, focusing on what happens after rollout.

We’ll explore common breakdown points, including low user adoption, unclear data ownership, and AI tools that don’t align with daily workflows. I’ll walk through real scenarios where initial approaches didn’t work, the constraints we faced, and the adjustments that delivered measurable results.

Attendees will leave with practical guidance on how to avoid common pitfalls, integrate AI effectively, and drive adoption across teams. This session is about decisions, trade-offs, and actionable strategies not theory/generic tool demos.