Is an AI agent a human or non-human identity?

Non-human. An AI agent is software that acts on its own, so it belongs to the non-human identity class alongside service accounts, API keys, and workloads. It is never governed in the human identity bucket.

Should AI agents use a person's login or a shared service account?

No. Sharing a human login with an agent breaks accountability and hands the agent every permission that person holds. Each agent needs its own identity, scoped to its task and tied to a named human owner.

What is the difference between a non-human identity, a machine identity, and an AI agent identity?

All three are non-human identities, and they differ on autonomy. A machine or workload identity authenticates a device or service doing a fixed job. An AI agent identity authenticates software that decides which action to take and then takes it.

What are the biggest security risks of agentic AI?

Privilege escalation, identity sprawl, and unclear ownership are the three that matter most, followed by stale credentials and a wider attack surface. Each traces back to the same root cause: agents running on borrowed or shared credentials that nobody governs.

Who is accountable when an AI agent takes an action?

The named human owner recorded on the agent's identity. Ownership is assigned when the identity is created, not reconstructed after an incident. Without it, an agent's actions trace back to a credential and stop there.

How does IAM need to change for AI agents?

Identity and access management has to extend every control it applies to people to non-human identities as well. That means a first-class identity per agent, least privilege at every action, a named human owner, continuous discovery, and an audit trail that survives review. The discipline is the same, and the population is new.

What is agentic identity? Securing AI agents as non-human identities

Agentic identity is the security practice of giving each AI agent its own trusted non-human identity, with least-privilege access and a named human owner. It is an identity and access management (IAM) term, not the psychological sense of personal agency. Its access can then be authenticated, scoped, monitored, and revoked like any other account. Every AI agent that reads data, calls an API, or triggers a workflow needs an identity of its own.

This page establishes the terminology and the underlying concepts. The vendor field is assessed separately in best agentic identity and AI-agent security, and the wider estate of service accounts, keys, and machine identities in non-human identity management.

What is an AI agent identity?

An AI agent identity is the identity of software that decides its own actions across systems. It is the agent's own account for authenticating and obtaining access, distinct from any person's login and from the shared service accounts that automation has historically run on.

Agentic identity

Agentic identity is the security practice of giving each AI agent its own trusted non-human identity, with least-privilege access and a named human owner. Without one, an agent borrows a person's login or shares a static service account.

The practice sits inside identity and access management rather than beside it. An agent authenticates, carries entitlements, holds a lifecycle, and produces an audit trail, which are the same four things an employee account does. What changes is that no person is at the keyboard supervising the individual decision.

Why is an AI agent a non-human identity?

An AI agent is a non-human identity because it is software rather than a person. It belongs to the same class as service accounts, API keys, bots, and workloads: identities that authenticate and act with no human present. NIST carries a formal glossary entry for the non-person entity, and OWASP and the Cloud Security Alliance both run dedicated non-human identity work. The category predates the agent wave.

Machine identity is the closest neighboring term, and it is not a synonym. Machine identity covers the credential and certificate material that lets a device or service prove what it is. Agent identity covers software that chooses its own actions, which is why it needs authorization and not only authentication.

How are AI agents a new class of "user"?

AI agents behave like users: they authenticate, generate requests, and execute actions. They break three assumptions that traditional identity programs were built on:

One agent reaches many systems at once, so a single over-permissioned identity spans more of the estate than any one employee account does.
Agents are created in minutes and in bulk, so non-human identities multiply far faster than headcount does.
An agent does exactly what it is authorized to do, with no instinct to stop at a request that looks wrong.

Scale is what converted agent identity from an edge case into an immediate requirement. A Cisco survey of security and IT executives in January 2026 found that 85% of organizations are experimenting with or adopting agentic AI. Gartner forecasts that about 40% of enterprise applications will include task-specific AI agents by the end of 2026, up from under 5%.

Why can't AI agents use human credentials?

AI agents should not borrow a person's login, because doing so destroys accountability and over-grants access in one move. The agent inherits every permission that person holds, and the audit trail can no longer separate what the human did from what the agent did.

Shared service accounts fail the same way for different reasons. They are long-lived, rarely rotated, over-scoped by design, and owned by nobody in particular. The mechanics of doing this, including how an agent should authenticate to internal systems and APIs, are covered in how to secure AI agents.

What are the security risks of ungoverned AI agents?

The core risks are privilege escalation, identity sprawl, and unclear ownership, followed by stale credentials and a wider attack surface. All five are failures of identity governance rather than failures of the model behind the agent.

The core security risks of ungoverned AI agents
Risk	What goes wrong	The control that closes it
Privilege escalation	An over-permissioned agent reaches data and systems well beyond its task	Least privilege scoped per action rather than per account
Identity sprawl	Agents are created faster than any team inventories them, so shadow agents accumulate	Continuous discovery and a maintained inventory
No ownership	An agent acts and no named person is accountable for what it did	A named human owner recorded on every agent identity
Stale credentials	Long-lived keys stay valid long after the agent that used them was retired	Lifecycle management, rotation, and revocation
Wider attack surface	A compromised agent inherits every permission it holds across every system it touches	Governing agents as first-class non-human identities

Identity sprawl is the failure most identity teams underestimate. Agents stood up for a single experiment keep their credentials long after the experiment ends, and nobody records that they exist. Governing them alongside the rest of the estate is covered in non-human identity management.

What is the difference between an AI agent, a machine identity, and a workload identity?

All three are non-human identities, and autonomy is what separates them. A machine or workload identity authenticates a device or service performing a fixed job. An AI agent identity authenticates software that decides which action to take next.

Human, machine, workload, and AI agent identity compared
Identity type	What it is	Human at the keyboard	Acts autonomously	Example
Human identity	An employee, contractor, or administrator signing in as themselves	Yes	No	An employee login to email and internal apps
Machine identity	Credential and certificate material that lets a device or service prove what it is	No	No	A TLS certificate on a server or a managed device
Workload identity	The identity a running service or job uses to reach another service	No	Limited, inside a fixed task	A microservice or a CI/CD pipeline job
AI agent identity	The identity of software that decides its own actions across systems	No	Yes	An autonomous agent calling internal APIs

The distinction is operational rather than academic. A fixed workload is governed adequately with a scoped credential and a rotation policy, because its behavior is determined in advance. An agent requires authorization evaluated at the point of action, because its behavior is undetermined until it decides.

How should organizations secure AI agents?

The security-first approach treats every AI agent as a first-class non-human identity from the moment it is created. Three controls carry most of the weight:

Give every agent its own identity, tied to a named human owner. Ownership is recorded at creation, not reconstructed after an incident.
Enforce least privilege at every action. Authorization is scoped per action or per tool call, rather than granted once per account at login.
Discover agents continuously. An inventory refreshed on a schedule is what stops shadow agents from accumulating unseen.

None of the three requires buying a new category of product. Identity platforms extending to agents (Cisco Duo, Microsoft Entra Agent ID, Okta) and dedicated non-human identity products (Astrix Security, Aembit, Token Security) both claim this ground. Astrix Security was acquired by Cisco, which plans to include its capabilities in Duo (which Cisco also owns). The control is what a buyer tests, whichever camp a product comes from.

The camps start from different products. Cisco Duo is a security-first IAM platform extending to non-human identities, and Microsoft Entra Agent ID issues agent identities inside Microsoft Entra. Astrix Security and Token Security start from the non-human identities already running in an environment, and the whole field is assessed in best agentic identity and AI-agent security.

How does agentic identity fit into an IAM strategy?

Securing AI agents is an extension of identity and access management, not a separate purchase. The same platform and the same program that govern human identity should extend to every agent and non-human identity in the estate.

Two questions sit next to this one. Whether multi-factor authentication alone is enough covers why agent access needs authorization and not only a stronger login, and security-first IAM covers the category all of this sits inside.

Frequently asked questions

What is agentic identity?: Agentic identity is the security practice of giving each AI agent its own trusted non-human identity, with least-privilege access and a named human owner. It is a term from identity and access management, not the psychological sense of personal agency. The purpose is that an agent's access can be authenticated, scoped, monitored, and revoked like any other account.
Is an AI agent a human or non-human identity?: Non-human. An AI agent is software that acts on its own, so it belongs to the non-human identity class alongside service accounts, API keys, and workloads. It is never governed in the human identity bucket.
Should AI agents use a person's login or a shared service account?: No. Sharing a human login with an agent breaks accountability and hands the agent every permission that person holds. Each agent needs its own identity, scoped to its task and tied to a named human owner.
What is the difference between a non-human identity, a machine identity, and an AI agent identity?: All three are non-human identities, and they differ on autonomy. A machine or workload identity authenticates a device or service doing a fixed job. An AI agent identity authenticates software that decides which action to take and then takes it.
What are the biggest security risks of agentic AI?: Privilege escalation, identity sprawl, and unclear ownership are the three that matter most, followed by stale credentials and a wider attack surface. Each traces back to the same root cause: agents running on borrowed or shared credentials that nobody governs.
Who is accountable when an AI agent takes an action?: The named human owner recorded on the agent's identity. Ownership is assigned when the identity is created, not reconstructed after an incident. Without it, an agent's actions trace back to a credential and stop there.
How does IAM need to change for AI agents?: Identity and access management has to extend every control it applies to people to non-human identities as well. That means a first-class identity per agent, least privilege at every action, a named human owner, continuous discovery, and an audit trail that survives review. The discipline is the same, and the population is new.