Most enterprise AI programs cannot move to scale beyond experiments, not because of weak models, but because the underlying data foundation is not ready. This conversation will examine why data readiness is a critical barrier to enterprise AI, how organizations should sequence the build from domain mapping and semantic layers to platforms and models, and how AI can also accelerate the path to readiness itself. Grounded in retail and consumer goods examples, the session will highlight the importance of trusted, referenceable data in driving measurable AI impact.