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013: AI

Implementation Effort: Low to Medium – Enabling AI-assisted experiences is usually straightforward, but governance, licensing, and human review processes need planning.

User Impact: Low – End users are usually unaffected; administrators gain assisted analysis and content-generation capabilities.

Overview​

AI-assisted experiences for Microsoft Intune can help administrators summarize device posture, understand policy impact, draft configurations, and investigate endpoint issues faster. In a Zero Trust model, the value of AI is not that it makes autonomous decisions, but that it helps humans analyze complex device and security data more consistently and quickly. Any AI feature used in Intune should still operate within approved permissions, human review, and data-governance boundaries.

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Implementation Guidance​

  1. Identify the supported AI or Copilot experiences currently available for your tenant and verify the required licensing, regional availability, and data-governance prerequisites.
  2. Define acceptable use for admins. Generated policy suggestions, summaries, or troubleshooting advice should be reviewed by a qualified operator before broad deployment.
  3. Use AI-assisted experiences first for lower-risk tasks such as summarization, investigation, and draft generation before relying on them in high-impact change workflows.
  4. Review role assignments and data exposure. AI tooling should not become a backdoor that lets a broad audience see more device or security data than they could otherwise access.
  5. Capture lessons learned from pilot use, including accuracy, saved time, and cases where the tool omitted important context.
  6. Align the feature with existing change control. AI can accelerate analysis, but final approval for policy changes should remain with authorized administrators.

Reference​