This article discusses the evolution of data governance from a rigid, compliance-focused approach to a more dynamic, context-driven model. It argues that as AI systems become more autonomous, organizations need to shift from controlling data to ensuring accountability and intentionality in how data is used. The author emphasizes the importance of negotiating meaning and maintaining oversight in increasingly complex socio-technical environments.