Enterprise data governance framework: components, roles, and AI readiness

This post details the components, roles, and AI readiness of an enterprise data governance framework. It emphasizes the importance of clear ownership, automation, and embedding governance into workflows. The post outlines core policies for data access, classification, retention, and privacy, and explains how semantic layers make these policies executable, especially for AI analytics. It also discusses centralized, federated, and hybrid governance models, and the roles of executive sponsors, data governance leads, councils, owners, and stewards. The impact of AI on governance is discussed, highlighting how AI can surface inconsistencies and how agents can aid in governance tasks.