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Microsoft is shifting AI governance from static documentation to dynamic runtime enforcement within production environments, integrating policy controls directly with observability and audit loops. This architecture leverages services like the AI Gateway to enforce security rules on agents and models without requiring code changes, ensuring continuous compliance as systems operate.

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Microsoft Moves AI Governance from Policy to Runtime Enforcement

InfoQAugust 24, 20263 min read

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 organizations verify governance requirements as AI applications and agents operate in production. By Leela Kumili

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…

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