Case study: Implement Adaptive Protection for AI data security

As organizations adopt generative AI tools, traditional security policies might not provide enough flexibility to manage evolving risks. Microsoft Purview Adaptive Protection helps address this challenge by adjusting data loss prevention (DLP) policy enforcement based on user risk signals. These signals can come from browsing behavior or how users handle data in AI environments. This dynamic approach helps protect sensitive information without blocking productivity across the organization.

The next example shows how a financial technology company uses Adaptive Protection to safeguard sensitive data while enabling responsible use of AI tools.

Learning objectives

In this example, you’ll learn how to:

• Use Adaptive Protection to manage data security risks related to AI tool usage.
• Link insider risk policies and DLP policies through dynamic user risk levels.
• Configure protections that block or restrict risky actions based on those levels.