Every AI Agent Needs an ID: Identity, Least Privilege, and Registries for Enterprise AI Agents

November 05, 2026

Sourjya Roy

November 05, 2026

Sourjya Roy

What is agent identity?

Agent identity is a distinct, verified identity assigned to each AI agent apart from the people and service accounts around it. It allows a business to authenticate each agent, grant it only the access needed for its mission, log each action under the agent’s own name and turn it off in one shot. Without it agents are running on borrowed or shared credentials that no one can trace.

In short: one agent/ account, one identity, one accountable owner, least privilege by default.

Why agent identity matters now

Agent identity appeared as a vendor category in a quarter. And that’s the question every security chief is asking today: Which agent did that, and who’s accountable for it?

Cloud platforms shipped it. Google Cloud assigns each agent a cryptographic identity following the SPIFFE standard. This identity is supported by an Agent Registry and Agent Gateway (Google Cloud). Microsoft designed Entra Agent ID for the same (Microsoft Learn).
Workflow platforms followed. In October 2026, ServiceNow introduced AI Passport, which provides each agent with a verifiable credential of its own (ServiceNow).
NIST weighed in. It announced 10 design tenets for agent identity management systems on October 27, 2026 (NIST).
Incidents are reaching the board. A survey by IBM indicated that 80% of large EMEA companies had an AI issue that went all the way to the board in the past year (Ashford Publishing).

Why service accounts and human IAM break for agents

The enterprises of the two identity models do not run fit agents. Human IAM assumes a person is logging in. Service accounts have a single predictable job. Agents choose their own steps, call tools at runtime, and frequently act for a user located several hops away.

The data reveals the gap. In a 2026 Aembit and Cloud Security Alliance poll, 68% of enterprises stated they couldn’t discern agent actions from human ones, and nearly three-quarters said agents had more access than they needed (Aembit).

	Human identity	Service account	Agent identity
Behavior	Directed by a person	Repeats one task	Picks its own next step
Lifespan	Years	Long-lived	Minutes to months
Credentials	Password, MFA, passkey	Often long-lived keys	Short-lived, task-scoped
Audit must show	Who acted	Which service called what	Which agent, for which user, on what instruction

Microsoft says that an agent can be produced and deleted thousands of times per day (Microsoft Learn). Google Cloud agent identities cannot be transferred between workloads, impersonated, or given long-lived keys (Google Cloud).

The agent identity framework: 8 pillars

Each pillar maps to the NIST design tenets, so the table doubles as a gap assessment.

Pillar	What it means	Key controls	NIST tenet
1. Unique identity	Each agent has its own verifiable ID	Per-agent IDs, no shared accounts	01
2. Ownership and registry	Every agent has a named owner and purpose	Agent registry, sponsor of record, lifecycle states	01, 10
3. Delegation and attenuation	Acting for a user carries both identities; authority only shrinks downstream	On-behalf-of tokens, scope narrowing for sub-agents	02
4. Zero standing privilege	No access when idle; minimum scope when active	Just-in-time, time-bound grants	03
5. Short-lived credentials	No static secrets; instant revocation	Ephemeral, certificate-bound tokens	04
6. Policy outside the model	The model proposes; deterministic policy decides	Gateway or policy engine	07, 08
7. Human-in-the-loop triggers	High-impact actions go to a person	Risk thresholds, approval workflows	05, 06
8. Monitoring and evidence	Every action watched and logged out of the agent’s reach	Anomaly alerts, append-only logs	09, 10

Pillars don’t work alone. NIST’s example: preventing a confused deputy attack takes delegation controls, least privilege, policy separation and deterministic access decisions together.

How major platforms approach agent identity

The platforms agree on the principle, every agent is its own principal, and differ on mechanics.

Platform	How identity is issued	Standout control
Google Cloud Agent Identity	SPIFFE ID with an X.509 certificate renewed every 24 hours	Tokens bound to the certificate, so stolen tokens cannot be replayed
Microsoft Entra Agent ID	Agent identities created from a blueprint that holds the credentials	Separate owner and sponsor roles; one policy covers every agent from a blueprint
IBM Agent Identity	Central registration and inventory	Works alongside Entra ID, Okta and HashiCorp Vault
ServiceNow AI Passport	A passport credential built on open specifications	Any governance tool can issue and verify it, including for third-party agents

Google and Microsoft employ delegated OAuth to differentiate autonomous agents, which use their own identities, from interactive agents operating on behalf of a signed-in user. Both audit logs display the agent and user together.

One rule works for all platforms: identity is not authority. An agent can be exactly who it claims to be while requesting something it is not permitted to do (Dock). NIST emphasizes the same point: keep what an agent tries separate from what it is permitted to do because guardrails alone are insufficient.

How to implement agent identity in 6 steps

Inventory. Find every agent involved in production, as well as the credentials they currently use. Shared accounts and static keys come first.
Register with an owner. Record the purpose, sponsor, data touched, and lifecycle status. No owner, no production access.
Issue unique identities. Use your platform’s native mechanism to retire shared credentials as each agent transitions.
Scope to the task. Begin with zero standing privilege and provide just-in-time access. For user-driven agents, include both identities in the token.
Enforce policy outside the agent. Route tool calls through a gateway with predetermined rules and thresholds for human approval.
Log, monitor, revoke. Keep append-only logs, configure agent-specific alerts, and ensure that a single action cuts an agent off everyplace.

Monitor the decommissioning process. On Google Cloud, IAM bindings on a deleted agent remain in policy until manually removed (Google Cloud).

Agent identity in practice: a worked example

Consider an illustration procurement agent who examines vendor quotes and creates purchase orders.

Registration- The agent is assigned its own identity, a specified procurement sponsor, and a limited scope: read vendor proposals and create orders only.
Authentication- When it calls the vendor system, it displays a temporary, certificate-bound credential. There is no API key in its settings.
Delegation- It requires pricing information, thus it engages a market-analysis sub-agent with read-only access to a single price database. The sub-agent can never have more authority than the parent.
Escalation- Any order that exceeds an approval threshold is routed to a human buyer before being sent out.
Audit- Each step saves the agent, the asking user, the instruction, and the result in a store that the agent cannot alter.
Revocation- If the agent behaves unusually, the sponsor disables its identity. Its access ends with the sub-agent’s delegated access.

Every pillar in the framework shows up in one ordinary workflow. That is the point: agent identity is plumbing, not a separate project.

Three common mistakes to avoid

Running agents on a developer’s token. It works in a demonstration. In production, every action appears to have been taken by that developer, and canceling the agent also locks the developer out.
Treating the system prompt as a security control. Prompt injection may override instructions. Enforcement must exist in a layer that the model cannot rewrite.
Forgetting retirement. Agents are often replaced. Without a cleanup process, old permissions build up as orphaned access that no one owns.

Agent identity readiness checklist

Agents who respond with fewer than six yeses are outpacing your controls.

Can we list all agents in production?
Does each agent have a designated human owner?
Does each agent have their own identity, rather than a common account or user token?
Do agents have zero standing privilege while idle?
Are agent credentials short-lived and without static secrets?
Do logs for delegated actions include both the agent and the user?
Is authorization enforced outside of the model?
Have we tested the ability to revoke a single agent across all locations?

Frequently asked questions

What is an AI agent identity?

A unique, verifiable identity for a specific AI agent, distinct from human users and service accounts, allowing every action to be authenticated, authorized, and traced back to the agent and its owner.

Why can’t AI agents just use service accounts?

Service accounts are frequently shared, have long-lasting keys, and lack enforced ownership. Agents are dynamic and act for several users, therefore shared accounts violate attribution and least privilege.

What is the difference between agent identity and authorization?

Identity determines which agent is acting. Authorization determines what it may perform in that setting. Before any high-impact action can take place, both must pass.

What is zero standing privilege for AI agents?

When the agent is not active, it has no access. It receives just-in-time, task-scoped access that expires when the task is completed.

How do AI agents act on behalf of users securely?

Through delegated authorization, such as the OAuth on-behalf-flow. The identities of the agent and the user travel together, limiting downstream power.

What is an agent registry?

A centralized inventory of all AI agents, including their identity, owner, purpose, permissions, and lifetime state. It is how teams identify shadow agents and retire unused ones.

What standards support AI agent identity?

SPIFFE for workload identity, OAuth 2.0 and OpenID Connect for delegation, and W3C Verifiable Credentials for cross-organizational trust. NIST issued 10 design principles in October 2026.

How do you revoke an AI agent’s access?

Disable the agent’s identity, let temporary credentials expire, and then remove any remaining permission bindings.

The bottom line

Agents are becoming coworkers with system access. The pattern is now clear: one agent, one identity, one owner, the least privilege, policy outside the model, and evidence that the agent cannot access. Teams that build on this foundation now avoid a hard refit in the future.

Sources

LLM Model Routing vs. Model Selection: Why Choosing the Best AI Model Is No Longer Enough

AI & Machine Learning