Guide: Protecting sensitive data from AI security risks

Organizations adopting AI tools face data security challenges as threat actors exploit vulnerabilities in GenAI platforms, enterprise AI applications, and autonomous agents. Breaches have exposed millions of confidential messages, credentials, and sensitive files—showing how AI systems can become targets without proper governance.

This guide explores AI-driven data risks and offers a framework for protection, including:

· Exploitation techniques targeting AI applications and datasets
· Governance roles and policies for securing enterprise AI
· Controls like DLP, DSPM, and insider threat management

Safeguard critical data while enabling AI innovation.