When AI Goes Live, Control Becomes the Real Problem

Enterprise AI doesn’t fail at launch—it drifts in production. Once deployed, models behave like infrastructure, quietly evolving as data and context change. Traditional program management tools fall short because AI requires continuous oversight, feedback loops, and clear ownership. Long-term success depends less on model accuracy and more on governance, observability, and maintaining organizational trust.