AI Risk Management

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M365 Native Shield:  Compliance Infrastructure in the Tools You Already Use.

Why AI risk management matters:

  • AI introduces new risks around data leakage, policy violation, hallucinations, and misuse of sensitive information.
  • Organizations need a structured way to manage AI risk before AI becomes embedded in everyday operations.
  • Effective AI risk management supports safer innovation and better regulatory readiness.

Architecture Overview:

  • We define AI risk domains across governance, data security, compliance, model use, and human oversight.
  • We align AI controls with existing Microsoft Purview, Microsoft 365, and broader security and compliance processes.
  • We create a framework for inventory, assessment, monitoring, and escalation of AI-related risks.

Key Capabilities:

  • AI risk assessments for use cases, data exposure, and control gaps.
  • Policy frameworks for acceptable use, sensitive data handling, and control enforcement.
  • Monitoring and governance reporting for AI activity, exceptions, and remediation actions.

Implementation Timeline:

  • Phase 1: AI inventory and risk scoping across business use cases.
  • Phase 2: design of the governance framework, controls, and responsibilities.
  • Phase 3: implementation, monitoring, and continuous improvement of the AI control environment.

Frequently asked questions

It is the process of identifying, evaluating, controlling, and monitoring risks created by AI use.

No; any organization using AI with business data should manage the risks.

Yes; Microsoft positions Purview as a platform for managing AI-related data security and compliance risks.

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