Identity serves as the control plane for AI operations by managing access and authorization dynamically rather than statically. This shift is crucial because traditional identity and access management (IAM) systems, designed for human users, struggle to scale with the increasing number of non-human identities. By rethinking identity management, organizations can ensure secure access to data and applications while minimizing risks.

Traditional IAM systems often rely on static roles and long-lived passwords, which become ineffective when non-human identities outnumber human ones significantly. These systems cannot adapt to the dynamic nature of agentic AI, where tasks and required data access can change frequently. This inadequacy can lead to security vulnerabilities, such as over-permissioned agents that can act without oversight.

Organizations should start by cataloging all non-human identities and issuing unique identities for each agent. Implementing just-in-time access with short-lived credentials can help manage permissions more effectively. Additionally, using synthetic data for testing and validation before moving to real data can provide a safer environment to establish and refine security policies.