AI Agents Are Privileged Users—Start Treating Them That Way

Darren Guccione, CEO and cofounder, Keeper Security.

The security industry has spent two decades building walls around human identities. Strong authentication, privileged access controls and least-privilege enforcement—these disciplines exist because we learned, through painful experience, that a compromised human account leads to a compromised organization.

​We’re about to learn the same lesson again. However, this time, the identities in question aren’t human. The ratio of machine and non-human identities (NHIs) to human identities has reached 144-to-1 in enterprise environments. NHIs grew 44% year over year—a surge tied directly to enterprises deploying LLMs, autonomous agents and API-driven workflows faster than they can track them. These agents are credentialed entities with access to critical systems, capable of making autonomous decisions and interacting with sensitive data at machine speed. Yet, most organizations have no centralized inventory or ownership model for them. and no governance framework that treats them with the same discipline applied to human privileged accounts.

It’s impossible for security teams to detect a compromised identity they have no visibility into, and it’s a growing issue as enterprises continue to deploy AI agents at scale.

A Sequencing Failure

There’s a pattern visible across organizations that have moved quickly on AI adoption, and it’s consistent enough to name. They deployed before they governed. AI agents went into production workflows, touching developer pipelines, customer systems and internal infrastructure, before anyone built the visibility layer that would let security teams see what those agents were doing or what they could access.

The Governance Model Exists

What gets lost in the urgency around AI agent security is the assumption that it requires an entirely new solution. In fact, the governance model already exists—we just built it for humans.