AI Data Governance for Production-Ready AI

AI governance matters when AI moves beyond pilots and starts affecting regulated, customer-facing, or operational decisions. The article explains how data ownership, lineage, access rules, bias monitoring, audit trails, and model lifecycle controls reduce compliance and accountability gaps. It also outlines why governance must be shared across business, data, technology, and risk teams. Technology leaders should treat governance as an operating model for scaling AI safely, not a documentation exercise.