AgentsAugust 24, 2026via InfoQ AI/ML
Microsoft Moves AI Governance From Policy to Runtime Enforcement
Why it matters
As agents move into production workflows, governance can't be a pre-deployment checklist — it has to happen live. Microsoft's architecture (policy + runtime enforcement + continuous eval + audit) is the infrastructure that makes agentic deployments auditable and compliant at scale.
Key signals
- Nine governance domains outlined
- Four governance functions: policy, control, visibility, proof
- Runtime enforcement (not just pre-flight policy)
- Continuous evaluation and observability during operation
- Identity, security, and audit evidence as first-class components
- Designed for production agents and AI applications
- Published August 2026 — current architecture guidance
- Four core functions: policy, control, visibility, proof
- Runtime enforcement tied to policy
- Continuous evaluation and observability as core components
- Identity, security, and audit evidence integrated
- Focus on production agent operation and verification
The hook
Microsoft shifts AI governance from the policy layer to runtime: nine domains, four functions, continuous enforcement as agents operate in production.
Microsoft has outlined an AI governance architecture spanning nine governance domains and four functions: policy, control, visibility, and proof. The approach connects policies with runtime enforcement, continuous evaluation, observability, identity, security, and audit evidence to help organization…