AI agents are being deployed across business systems at a breakneck pace—calling APIs, pulling data, and acting autonomously—often without the same checks and constraints we use for human users. Yet many security teams lack full visibility into who these agents are, what systems they touch, and whether their permissions are still appropriate.
An Okta report reveals that barely half (47%) of CISOs believe they can identify every AI agent in their environments. Even among those who feel confident about their visibility, about four in five are concerned that some agents may have excessive permissions that go unreviewed. Clearly, seeing an agent isn’t enough if you don’t also govern what it can do.
Why “Old School” Controls Don’t Cut It
Many organizations still rely on service-account models and shared credentials—tools designed for historic identity management—to secure AI agents. But those methods fall short when trying to answer key questions: Which agent can access what? Who approved that access? Is the access still needed? And most importantly, can you remove permissions without breaking things?
Only 25% of companies have adopted frameworks purpose-built for AI agent security. About one in five are still using broad, overpowered service accounts or shared credentials that grant blanket permissions. These gaps leave environments exposed and make maintaining control much harder as AI agent use grows. A better approach treats every AI agent as its own identity: separate ownership, audited permissions, a clear lifecycle, and regular access reviews.
Shadow AI Isn’t Solved by Blocking Alone
Shadow AI refers to tools and agents in use without going through standard approval channels. Trying to block these agents outright risks stifling innovation and adoption—but ignoring them exposes you to unpredictable security risks. The solution: discover what’s out there, map out what each agent can do, assign clear ownership, and bring everything under a unified control model.
Organizations with mature identity governance report fewer incidents of shadow AI, quicker response when rogue agents emerge, and less worry over AI-incurred breaches. Identity governance isn’t just about prevention—it’s about containment and adaptability when risk levels change.
A webinar led by Okta’s leadership will walk through how to formally treat AI agents as first-class identities, shut down excessive permissions, and gain control over shadow AI before it spins out of control. Key topics include aligning visibility with authorization, implementing identity governance practices, and becoming responsive to changes in risk.
It’s time to recognize that securing AI agents is fundamentally about identity governance. Knowing which agents exist means nothing if you haven’t also defined what they can do or how fast you can revoke access when it’s no longer appropriate.
Why this matters: As AI agents proliferate, so does the risk of unchecked data access, privilege creep, and accidental exposure of sensitive systems. Organizations that proactively govern permissions—and bring all agents into identity frameworks—are in a far stronger position to prevent breaches, manage compliance, and maintain trust.
