Treat AI agents as a distinct identity class before security and compliance gaps become incidents.
AI agents can interpret goals, make decisions, and act across systems at machine speed, often with limited human oversight.
That autonomy creates risks traditional identity programs were not designed to manage. This eBook explains why agents require their own identity class and shows security leaders how to govern access at runtime, protect credentials outside the agent, scope permissions to current behavior, and capture session-level activity for stronger security and compliance.
This Securing Agentic AI eBook provides:
- A clear explanation of why AI agents differ from human users, service accounts, and traditional machine identities.
- Insight into the classification, credential storage, lifecycle, and audit gaps that can expose sensitive systems.
- Four practical requirements for runtime authorization, behavioral controls, credential injection, and session-level accountability.
- Three diagnostic questions security leaders can use to assess and strengthen agent identity governance.