Microsoft Moves AI Governance From Policy to Runtime Enforcement

Microsoft has outlined an AI governance architecture that moves governance from documented policies toward runtime enforcement, continuous evaluation, observability, and audit evidence as organizations deploy AI applications and agents in production. The framework spans nine governance domains and four functions: policy, control, visibility, and proof, addressing the need to verify that governance requirements are enforced and observable during AI system operation.

Microsoft AI governance architecture (Source: Microsoft Blog Post)

The architecture treats governance as a continuous operational loop. Policies establish requirements and risk classifications, controls translate them into access and runtime rules, observability captures system behavior, and evaluations test quality and safety. Audit processes then turn operational telemetry into evidence for compliance and incident investigation.

Manasa T. Ramalinga, Cloud Solution Architect at Microsoft, described the…