Identity serves as the control plane for agentic AI by evolving from a simple login gatekeeper to a dynamic system that manages access and authorization in real-time. This shift is essential because traditional identity and access management (IAM) methods, which were designed for human users, are inadequate when non-human identities can outnumber human ones significantly. By making identity central to AI operations, organizations can better secure their systems and manage access effectively.

Traditional IAM systems are failing because they rely on static roles and long-lived passwords, which do not adapt to the dynamic nature of agentic AI. As AI agents can change tasks and data access needs frequently, fixed roles become a vulnerability. To address this, organizations need to implement continuous, runtime evaluation of access policies, ensuring that permissions are granted based on current context and purpose.

Organizations can enhance the security of AI agents by issuing unique, verifiable identities linked to specific business use cases and human owners. They should replace static roles with session-based, risk-aware permissions that are granted just in time and automatically revoked after use. Additionally, implementing context-aware authorization and embedding policy enforcement directly into the data query engine can help ensure that access is purpose-bound and secure.