Organizations worldwide are accelerating their investment in artificial intelligence (AI), yet many struggle to define what success actually looks like once a system goes live. This article introduces a practical, four-dimensional framework for measuring true AI adoption, covering workflow efficiency, decision quality, cultural adoption, and responsible AI practices. Grounded in established technology acceptance theory and sociotechnical systems thinking, the framework is operationalized through an AI Adoption Maturity Assessment (AAMA) framework that generates targeted recommendations for data team leaders. The goal is to give students, early-career engineers, and organizational leaders a clear, actionable approach to evaluating AI initiatives beyond deployment milestones.