AI agents are here. Your identity strategy isn’t ready.

AI agents don’t behave like humans. They don’t behave like machines. They’re something entirely new, and that’s exactly the problem.

These autonomous, goal-seeking entities are capable of reasoning, deciding, and acting on their own. They spin up in minutes, operate 24/7, and make millions of decisions per hour. With access to sensitive systems and data, they don’t follow predefined workflows or wait for human direction. They execute. Relentlessly.

While human identities are onboarded through HR systems and machines follow structured, predictable rules, AI agents operate with human-level intelligence at machine speed. They don’t show up in your HRIS. They’re not provisioned through traditional IT channels. And yet, they are rapidly multiplying across enterprise environments, often without anyone noticing.

This shift is creating a crisis of speed and scale in identity governance and security.

Traditional identity playbooks are breaking

Identity programs were designed around two fundamental models: human users and machine accounts. Both come with clear ownership, predictable behavior patterns, and lifecycle hooks for onboarding, offboarding, and access management.

AI agents don’t fit these models. They're ephemeral, dynamic, and self-directed. They use OAuth tokens and SSO credentials, bypass traditional provisioning processes, and often act outside established governance frameworks. They're already operating in your environment: connecting to APIs, ingesting data, and making decisions with far-reaching consequences.

Manual oversight doesn’t scale here. Static roles and infrequent access reviews won’t keep up. And the further enterprises lean into AI, through copilots, assistants, and intelligent automation, the wider this visibility gap grows.

A new identity model for autonomous agents

Two central security and governance problems have emerged in my conversations with business leaders: How do you ensure that agents are bound by the same entitlements as the humans they represent, and how do you ensure that humans don’t get access to more data than they are permitted through the agents they are accessing?

To solve these problems and secure AI agents more broadly, we need to redefine what governance looks like. That starts by treating these agents as first-class identities—just like humans and machines—but governed according to their unique behaviors and risks.

Here’s what that requires our industry to work towards:

• Governing the entire access chain. You can’t secure what you can’t see. You need visibility into the non-deterministic agent access pathways: Human User/Owner –> Agent -> Machine -> App -> Data -> Cloud resources, or different combinations of this chain.
• Real-time policy engines. Organizations need continuous visibility into every agent in their environment: what it’s doing, where it’s operating, and what it can access, to be able to enforce policies in real-time.
• Short-lived credentials and dynamic scoping. Agents must operate with the least privilege possible. That means short-lived, narrowly scoped credentials that expire quickly and don’t grant persistent access.
• Just-in-time, context-aware access controls. Access should be granted only when needed, and only if contextual signals (like location, workload, or user approval) support it.
• Continuous, behavioral monitoring at machine speed. Governance doesn’t stop at access control. Continuous, real-time monitoring is essential to detect anomalous behavior and stop agents that go off-script before they cause harm.
• Assigned accountability. Every AI agent should have a designated human owner responsible for reviewing its activity, governing its access, and decommissioning it when it’s no longer needed.

Ask the hard questions

Despite the growing adoption of AI agents, most organizations still can’t answer some of the most basic questions, like:

• How many AI agents are operating in your environment right now?
• What systems do they have access to?
• Who is responsible for managing them?
• Can you stop them if they begin to behave unexpectedly?

If your identity strategy doesn’t account for AI agents, the answer to most of these questions is likely “no.”

The agent economy has arrived

This isn’t a future problem. Thousands of AI agents are already active in enterprise environments, deployed by business units, third-party platforms, and external vendors. Some are governed. Most are not.

If you can’t govern it, you can’t secure it.

At SailPoint, we believe AI agents must be brought into the fold of identity security: monitored, controlled, and governed with the same rigor as any other identity. But doing so requires a shift from manual oversight to intelligent automation. From static controls to real-time enforcement. From old playbooks to new models.

The agent economy is already here. Now it’s up to identity leaders to catch up.