The GenAI Production Cliff: Why 95% of Pilots Fail (and How Databricks Helps You Join the 5%)
If you’ve felt that your company’s GenAI pilot is stuck somewhere between a promising demo and a PowerPoint slide that never turned into revenue — you’re not alone. Industry reports estimate that around 95% of enterprise GenAI initiatives fail to reach meaningful production . That’s not because the models are dumb. It’s because the process is. The GenAI Divide: It’s Not the Model, It’s the Method Every decade in tech has its cautionary tale. In the 1990s, it was software projects collapsing under their own weight — endless waterfall cycles, unclear requirements, and heroic debugging sessions at 2 AM. Today, it’s AI pilots : big budgets, slick prototypes, and then… silence. The truth is that most GenAI failures have nothing to do with bad models . They fail because of vague goals, poor data pipelines, and nonexistent engineering discipline . Let’s call it what it is: the GenAI Divide — a chasm between the flashy pilot and the governed, scalable product that enterprises actually ne...