Governing Entra‑Registered AI Apps with Microsoft Purview

As the enterprise adoption of AI agents and intelligent applications continues to accelerate, organizations are rapidly moving beyond simple productivity tools toward autonomous, Entra‑registered AI workloads that can access, reason over, and act on enterprise data. While these capabilities unlock significant business value, they also introduce new governance, security, and compliance risks—particularly around data oversharing, identity trust boundaries, and auditability.
In this context, it becomes imperative to govern AI interactions at the data layer, not just the identity layer.

This is where Microsoft Purview, working alongside Microsoft Entra ID, provides a critical foundation for securing AI adoption—ensuring that AI agents can operate safely, compliantly, and transparently without undermining existing data protection controls.

Lets look at the role of each solution Entra ID vs Microsoft Purview 

A very common misconception is that Purview “manages AI apps.” In reality, Purview and Entra serve distinct but complementary roles:

Microsoft Entra ID

• Registers the AI app
• Controls authentication and authorization
• Enforces Conditional Access and identity governance

Microsoft Purview

• Governs data interactions once access is granted
• Applies classification, sensitivity labels, DLP, auditing, and compliance controls
• Monitors and mitigates oversharing risks in AI prompts and responses
• Microsoft formally documents this split in its guidance for Entra‑registered AI apps, where Purview operates as the data governance and compliance layer on top of Entra‑secured identities.

Lets look at  how purview governs the Entra registered AI apps.

Below is the high level reference architecture which can be extended to low level details

1. Visibility and inventory of AI usage

Once an AI app is registered in Entra ID and integrated with Microsoft Purview APIs or SDK, Purview can surface AI interaction telemetry through Data Security Posture Management (DSPM).

DSPM for AI provides:

• Visibility into which AI apps are being used
• Which users are invoking them
• What data locations and labels are touched during interactions
• Early indicators of oversharing risk

This observability layer becomes increasingly important as organizations adopt Copilot extensions, custom agents and third‑party AI apps.

2. Classification and sensitivity awareness

• Purview does not rely on the AI app to “understand” sensitivity. Instead the Data remains classified and labeled at rest.
• AI interactions inherit that metadata at runtime
• Prompts and responses are evaluated against existing sensitivity labels

If an AI app accesses content labeled Confidential or Highly Confidential, that classification travels with the interaction and becomes enforceable through policy. This ensures AI does not silently bypass years of data classification work already in place.

3. DLP for AI prompts and responses

One of the most powerful but yet misunderstood purview capabilities is the AI‑aware DLP.

Using DSPM for AI and standard Purview DLP:

• Prompts sent to AI apps are inspected
• Responses generated by AI can be validated
• Sensitive data types (PII, PCI, credentials, etc.) can be blocked, warned, or audited
• Policies are enforced consistently across M365 and AI workloads

Microsoft specifically highlights this capability to prevent sensitive data from leaving trust boundaries via AI interactions.

4. Auditing and investigation

Every AI interaction governed by Purview can be recorded in the Unified Audit Log, enabling:

• Forensic investigation
• Compliance validation
• Insider risk analysis
• eDiscovery for legal or regulatory needs

This becomes critical when AI output influences business decisions and regulatory scrutiny increases. Audit records treat AI interactions as first‑class compliance events, not opaque system actions

5. Oversharing risk management

Rather than waiting for a breach, Purview proactively highlights oversharing patterns using DSPM:

• AI repeatedly accessing broadly shared SharePoint sites
• High volumes of sensitive data referenced in prompts
• Excessive AI access to business‑critical repositories

These insights feed remediation workflows, enabling administrators to tighten permissions, re‑scope access, or restrict AI visibility into specific datasets.

In a nutshell, With agentic AI accelerating rapidly, Microsoft has made it clear that organizations must move governance closer to data, not embed it into individual AI apps. Purview provides a scalable way to enforce governance without rewriting every AI workload, while Entra continues to enforce who is allowed to act in the first place. This journey makes every organizations adopt Zero Trust at scale as its no longer limited to users, devices, and applications;  It must now extend to AI apps and autonomous agents that act on behalf of the business.

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