Why AI agents need identities
AI agents differ from earlier automation in a way that matters for identity: they decide their own next actions. A scripted job calls the same API with the same parameters every night; an agent reasons about a goal and may choose to read a database, call a payment API, or send an email — sequences no one explicitly programmed.
When such an agent operates under a human's credentials or a shared service account, three things break. Attribution disappears: logs show the human acting, not the agent. Least privilege disappears: the agent inherits everything the human can do rather than the narrow slice it needs. And revocation gets dangerous: cutting off a misbehaving agent means cutting off the person or every workload sharing the account.
Giving each agent its own identity restores the basics: distinct credentials, scoped permissions, individual audit trails, and an owner accountable for what the agent does. In this sense agent identity is the newest branch of non-human identity, alongside service accounts and workload identities — but with autonomy that raises the stakes.
What governing agent identities involves
Governing an agent identity follows the same lifecycle as any identity, adapted to autonomy. Registration comes first: each agent is recorded with an owner, a purpose, and a defined scope of allowed actions before it touches production systems. Credentials should be short-lived tokens obtained through standard flows rather than long-lived API keys embedded in configuration.
Authorization needs to be narrower than for human users, because agents can be manipulated: prompt injection can steer an agent into attempting actions its author never intended, so the permission boundary — not the agent's judgment — must be what prevents damage. Sensitive actions can require human approval, and delegation should be recorded: when an agent acts on behalf of a user, both identities belong in the audit trail.
Finally, agents need lifecycle discipline: review of their access like any other identity, and prompt deprovisioning when the agent or its use case is retired — otherwise agents become the next generation of orphaned accounts.
AI agent identity in practice
Most organizations are early on this curve, and the pragmatic first steps mirror the early days of service account governance. Inventory the agents already running — many arrive embedded in SaaS products or built by individual teams — and identify what credentials they currently use. Anywhere an agent shares a human's account, separate it.
Then apply the basics deliberately: an owner per agent, scoped credentials per agent, expiry on everything, and logging that distinguishes agent actions from human actions. Standards in this space are still forming, with OAuth-based patterns such as token exchange for delegation emerging as the practical foundation.
Identity platforms are beginning to support this population natively, adding the ability to register agent identities and govern their access alongside human and machine identities.