Authored by vicperdana, this article explores how Microsoft Purview streamlines AI data governance and compliance, mitigating GenAI risks for enterprises.

Introduction

As artificial intelligence becomes integral to software development, organizations face a new set of data governance challenges. AI’s potential to accelerate innovation is tempered by risks around data leakage, regulatory compliance, and customer trust. In response, Microsoft presents clear solutions through Purview, its enterprise data governance platform, focusing on AI-driven applications and generative AI (GenAI).

This summary, based on the 7th episode of Microsoft’s ‘Security for Software Development Companies’ webinar series—featuring Kyle Marsh and Vic Perdana—explains how Microsoft Purview enables secure, compliant, and auditable AI deployments with minimal developer effort.

Current Landscape: Security Concerns in AI

A recent ISMG Generative AI Study highlighted business leaders’ top concerns:

  • Data leakage (82%)
  • Hallucinations and ethical issues (73%)
  • Regulatory confusion (55%)

Nearly half of respondents indicated they would ban AI if these risks persisted.

Microsoft Purview for AI: Extending Governance Capabilities

Microsoft has expanded Purview beyond traditional data to provide governance for AI use cases, covering enterprise tools like Microsoft Copilot as well as custom and third-party GenAI models such as Google Gemini and ChatGPT.

Key features include:

  • Data Loss Prevention (DLP): Applies to user prompts and AI responses.
  • Blocking Sensitive Content: Real-time prevention of policy violations.
  • Audit and Reporting: Tracks all AI activity.
  • Microsoft Graph API Integration: Enables programmatic access for developers.

Purview’s design means software teams leverage robust security without needing to build bespoke compliance frameworks.

Centralized Oversight: The Purview AI Hub

The AI Hub within Microsoft Purview offers centralized visibility over:

  • All AI interactions (Copilot, Azure OpenAI, third-party models)
  • DLP rule violations in real-time
  • Insider risk management
  • Monitoring of sensitive data usage and sharing

This allows organizations to comprehensively audit and control AI activity across their digital landscape.

Developer Integration: Microsoft Graph APIs

Integration is streamlined for developers through the Microsoft Graph APIs:

  • protectionScopes/compute: Determines when/why prompts or responses should be reviewed, returning modes like evaluateInline (await Purview response before proceeding) or evaluateOffline (send for audit in parallel).
  • processContent: Submits content for analysis; triggers DLP-driven block or allow responses.
  • contentActivity: Logs metadata for non-intrusive auditing.

This integration enables developers to enforce enterprise data policies with minimal extra code.

Example: Blocking Confidential Content in Copilot

A demonstrated scenario showed Microsoft Copilot intercepting a user query that would have exposed confidential “Project Obsidian” documents. Purview policies blocked the transaction, preventing data leakage.

Native Integration with Microsoft Tools

  • Copilot Studio: Fully automatic Purview integration.
  • Azure AI Foundry: Supports evaluateOffline by default, with options for deeper control.
  • Custom Apps: Can connect using Microsoft Graph APIs, adding enterprise readiness to bespoke solutions built with OpenAI APIs or similar.

Enterprise Policy Management

Through the Purview interface, organizations can:

  • Define custom sensitive information types
  • Apply role-based and location-aware access
  • Set policies for blocking or allowing data flows
  • Conduct audits, investigations, and eDiscovery

Developers need only respond to the decision returned by Purview’s API—no manual rule management is necessary.

Resources for Implementation

Microsoft provides:

Conclusion: Secure AI Builds Enterprise Trust

The article emphasizes that securing AI applications is essential—not optional—for enterprise adoption. Microsoft Purview, with its robust governance and seamless developer integration, enables organizations to build and scale AI solutions that balance innovation with compliance and data protection.

Watch the full webinar episode: Safeguard Data Security and Privacy in AI-Driven Applications

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