AI Data Security
with Microsoft Purview
AI assistants can surface information that once required a user to know exactly where to look, which means existing gaps in data governance become far easier to find and use. Explore how Microsoft Purview helps you classify sensitive information, prevent inappropriate sharing, and reduce oversharing before AI adoption moves ahead of your data security.


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Discover how to:
Understand your data estate and what AI can reach
Apply sensitivity labels and classification to establish data context
Prevent data loss and manage risky prompts with Microsoft Purview
Address oversharing and insider risk before scaling AI adoption




AI Data Security with Microsoft Purview
Employees can paste financial figures, customer details, or confidential project information directly into an AI prompt without a second thought, and that data needs protecting just as much as anything stored in a document. In this guide, we cover how Microsoft Purview addresses the full data lifecycle around AI, from sensitivity labelling and DLP through to insider risk and investigation.
Classify Sensitive Data
Apply sensitivity labels so AI only surfaces information based on its true classification.
Prevent Data Loss
Use Data Loss Prevention policies to control how sensitive information is shared once AI retrieves it.
Reduce Oversharing
Identify permissions that have accumulated over time and now sit exposed to AI-driven discovery.
Written by Microsoft MVPs
Insights from Threatscape's award-winning Microsoft Security Practice.
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