Identity serves as the control plane for AI operations by managing access and authorization dynamically rather than statically. This shift is crucial as 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 and efficient operations as they deploy agentic AI.

Traditional IAM systems are limited because they rely on static roles and long-lived passwords, which do not adapt to the dynamic nature of agentic AI. As non-human identities can outnumber human ones significantly, these legacy systems create vulnerabilities that can lead to unauthorized access and data breaches. A more flexible, runtime evaluation of access policies is needed to address these challenges.

Organizations can enhance the security of their AI agents by issuing unique, verifiable identities for each agent, implementing session-based permissions that are granted just in time, and mandating short-lived credentials. Additionally, using synthetic data for testing and validation before moving to real data can help ensure that access controls are effective and that any potential risks are mitigated.