Traditional data security relied on defined boundaries, but the AI era has dissolved these perimeters. Sensitive data now flows freely between trusted and untrusted applications, including generative AI tools, expanding the risk surface. Existing data loss prevention methods often fail to provide real-time visibility and enforcement, acting too late. Deploying traditional network appliances is also complex and costly. Microsoft Purview and Microsoft Entra are introducing a public preview to extend data security to the network layer. This integration offers real-time, identity-aware enforcement for data in transit. It detects sensitive data shared with shadow AI, unmanaged SaaS, and personal cloud repositories. Policies can dynamically block or limit exposure based on user identity, activity, and data sensitivity. This unified approach correlates signals across Microsoft Purview, Entra, and Defender for streamlined investigations. Organizations gain network-level visibility to prevent data leakage to risky locations like consumer AI apps. Protection is now preemptive, detecting and blocking sensitive data before it is exposed. This shift enables real-time data protection within the flow of user activity, securing data wherever it moves.