Microsoft Unveils Architecture for Automatically Applying AI Governance at Runtime

Microsoft announced a new architecture for applying and validating governance requirements in real time during the operation of AI systems. The architecture comprises nine governance domains and four capabilities—policy, control, visibility, and proof—and is designed to enable organizations to verify governance requirements even as AI applications and AI agents are actively running.

Until now, most organizations have primarily taken an approach of documenting rules for AI usage and conducting checks and audits retroactively. However, with the proliferation of generative AI and AI agents, scenarios in which AI makes autonomous decisions and takes actions are increasing, and cases are emerging where post-hoc verification cannot keep pace with demand. Many enterprises have faced the challenge of understanding in real time how rules are actually reflected in system behavior.

The architecture presented by Microsoft employs a mechanism that directly links policies to runtime controls. Specifically, continuous assessment, observability (a mechanism for understanding system internal operations), identity management, security, and audit trail generation are integrated as a unified workflow. This makes it possible to track compliance with rules even while AI is operating and to record them as evidence.

Particularly noteworthy is the positioning of the "proof" capability. By embedding a mechanism to continuously generate evidence that governance requirements are being met, it becomes easier to fulfill fact-based accountability to regulators and internal audit functions. The ability to record and present actual operational conditions, not merely policy definition in documents, positions this approach as having high practical value from the perspective of regulatory compliance.

Regarding AI governance, regulatory frameworks are being developed across countries and regions, and enterprises increasingly face requirements for transparency assurance and record retention. In this context, the approach Microsoft has put forward represents a shift in positioning—moving governance from the stage of "defining policy" to the stage of "automatically applying and recording in the place where systems operate."

Key points for future observation are how this architecture will be delivered as actual products or services and how other enterprises and industries will adopt and reference it. The importance of runtime governance application increases as AI agents become capable of operating across multiple business processes. Microsoft's initiative has the potential to influence discussions about governance standardization across the industry.