Secure the data behind your AI transformation
AI doesn’t replace the fundamental challenges of data security—it intensifies them. New AI services and agents are gaining access to existing enterprise data, while new datasets and authorization layers make it increasingly difficult to understand where sensitive information resides, who can access it, and whether it is adequately protected.
In this ebook, Palo Alto Networks’ Dan Benjamin explores how organizations can address these challenges by evolving DLP, moving from data exposure to real-time response, and bringing data, identity, and AI security together.
What you’ll learn:
- Map your enterprise data risk: Understand the three critical questions—what data you have, who can access it, and whether it is protected.
- Modernize DLP for the AI era: Protect sensitive data as it moves across endpoints, browsers, email, applications, and AI services.
- Turn visibility into action: Move beyond posture to detect suspicious data activity and accelerate response and remediation.
- Reduce security fragmentation: Learn why consolidating data security capabilities can simplify operations and help establish more consistent protection.
- Connect data, identity, and AI: Understand why securing AI depends on securing both the data it uses and the identities that can access it.
