Why autonomous AI agents and non-human identities need first-class status in enterprise IAM
Non-human identities (NHI) do not need to be human.
But they must be users in IAM — the Identity and Access Management layer enterprises use to govern who or what can access systems.
Not users in the social sense. Not employees. Not people. Not personas.
A user is not always a natural person. In many systems, a user is an entity that can utilize or operate the system and to which permissions, groups, roles, policies, and audit logs can be attached.
An agent can be a user without being a human user.
This distinction matters because many people associate “users” only with sign-on. In that view, a user is a human logging into an application through SSO. But IAM is broader than authentication. It is the governance layer for actors that can access, operate, or affect systems.
That is not unusual. Root, admin, and other operational accounts are often represented as users even when they represent operational roles rather than one-to-one human identities. What matters is that they are controlled, scoped, owned, and auditable.
Users in the identity-governance sense: first-class subjects that can be authenticated, authorized, owned, reviewed, audited, disabled, revoked, and held accountable through policy.
That distinction matters — because many organizations are about to repeat the same mistake with AI agents that they made with earlier automation: letting useful non-human actors operate through secrets, tokens, scripts, shared service accounts, or borrowed human sessions.
Autonomous agents are not traditional workloads. A workload usually executes predefined code paths. An agent may interpret context, select tools, make decisions, and trigger actions. If it behaves like a user inside enterprise systems, it must be governed like one.
If agents are expected to operate inside enterprise IT, they need to exist inside enterprise IAM.
Letting them operate through secrets, tokens, scripts, shared service accounts, or borrowed human sessions may be convenient.
It is not governance.
If an AI agent — or any bot, automation, integration, or legacy workload — can access systems and perform actions, it must be visible to IAM as an actor.
A non-human identity does not need a human name, a mailbox, a job title, or an HR record. But it does need IAM representation strong enough to answer the basic governance questions:
- What is this actor?
- Who owns it?
- What can it access?
- Why does it exist?
- When should it expire?
- How can it be revoked?
- Which group, role, or policy class does it belong to?
- Is it human-supervised, and who or what is responsible for that supervision?
Until IAM can answer those questions, the organization does not have governed agents — only activity attached to identities the business cannot properly see.
Start With the Directory
You do not need to implement a full agent-native identity system to start governing agents.
This is not the same as simply enabling SSO or generating tokens. Many teams use SSO platforms like Okta as shorthand for identity, but SSO mainly handles authentication. Governing agents requires the full identity management layer: ownership, classification, access review, auditability, policy enforcement, and revocation.
Create a user in the directory for each meaningful agent.
A meaningful agent is any agent that performs work which would require governance if performed by a human user: accessing sensitive data, processing regulated information, interacting with production systems, triggering workflows, calling privileged tools, or acting as the principal agent responsible for a business or technical outcome.
Assign it to a group that clearly identifies it as an “Agent”.
Then use additional groups, roles, or attributes to express important governance characteristics: human-supervised, fully automated, read-only, tool-enabled, production-facing, experimental, high-privilege, or delegated-action capable.
This may sound basic, but that is exactly the point. You need agents to be visible, classified, ownable, and reviewable before they perform any action.
Just adding agents to the directory as users and placing them in the right governance groups before they do anything is already a huge step toward real auditability, access review, policy enforcement, and incident response.
It does not solve the entire agent identity problem.
But it creates the first control point.
This approach is not a complete agent identity architecture. It is the minimum viable foundation: making meaningful, stable agents visible, ownable, classifiable, reviewable, and revocable in existing IAM before they perform any action.
Not every ephemeral task, prompt chain, or runtime instance needs its own directory user, just as every human session does not become a separate human identity. The durable agent that owns behavior, permissions, and accountability does.
A meaningful autonomous agent should therefore exist as a stable IAM user, much like any other durable enterprise actor. Its runtime instances should remain attributable to that identity, while temporary subagents should operate under explicitly delegated and bounded authority. Only a subagent that becomes a persistent, independently owned and governed actor should require its own stable IAM identity.
Runtime sessions, delegations, tool calls, and execution traces need granular representation in temporal, agent-native, or future IAM-extension layers built around that principal.
Do Not Let Agents Borrow Human Identity
This is also why an agent must not run under a human identity or borrow a user session.
If an agent acts through a human session, the audit trail may show the human, but not the agent that interpreted the context, selected the tool, triggered the workflow, or performed the action.
That breaks accountability.
A governed agent may act on behalf of a human. It may operate under delegated authority. But the agent itself must remain visible as an actor.
IAM Is the Principal Layer
In the broader agent identity model, the stable IAM identity is the bare minimum: the durable foundation.
Temporal layers — runtime instances, sessions, delegation, tool calls, policy decisions, and execution traces — are essential, but they cannot replace it.
Without a stable IAM principal, there is no durable actor to govern.
This is also what makes IAM the common governance and interoperability layer for agent identities across hybrid environments where humans, agents, legacy applications, cloud systems, directories, workload identities, and multiple agent-native identity providers — often heterogeneous — already coexist and will continue to coexist.
Even in greenfield or agent-native environments, a common IAM principal layer remains essential for consistent governance and interoperability.
This does not replace modern workload identity mechanisms such as managed identities, service principals, certificates, mTLS, or SPIFFE. Those remain valuable for authentication, short-lived credentials, and runtime security.
The point is different: autonomous agents still need a stable, governable IAM principal for ownership, classification, access review, auditability, and revocation.
Directory identity and workload identity are not competing layers. They should work together.
Emerging Industry Approaches
Current IAM will coexist with agent-native identity solutions. Enterprise governance will need both: stable IAM principals for ownership and accountability, and agent-native layers for granular runtime control.
Emerging approaches such as Enterprise-Managed Authorization (EMA) for the Model Context Protocol (MCP) and signed Agent Cards in the Agent2Agent (A2A) Protocol address important parts of the problem, including centralized access control, inter-agent trust and verification of published agent metadata. But these mechanisms do not, by themselves, fully answer the core enterprise-governance question: Which durable actor does the organization own, classify, review and hold accountable?
Enterprise governance therefore requires stable autonomous agents to be represented as first-class IAM users. Runtime instances and temporary subagents can receive bounded authority from that principal while remaining individually attributable in execution and audit records.
EMA further illustrates this point. By enabling organizations to govern access to MCP servers centrally through their existing identity provider, it reduces reliance on shared service accounts and long-lived tokens.
User-scoped identity does not inherently mean human-scoped identity. Where an enterprise IdP and participating EMA implementations support non-human subjects, a stable autonomous agent can be represented as a durable IAM user whose identity serves as the governance anchor for its access to MCP servers — and, through them, the services and tools they expose. Runtime instances and delegated subagents should remain attributable to that principal while operating within their own bounded execution contexts and delegated authority.
For fully autonomous machine-to-machine scenarios, MCP’s Client Credentials extension enables application-level authentication without an interactive human user. Those credentials should be explicitly bound to the agent’s stable IAM principal rather than treated as standalone application secrets.
In March 2026, A2A Protocol v1.0 introduced signed Agent Cards, enabling cryptographic verification of published agent metadata across organizational boundaries. This is a meaningful step forward in agent-native identity. But Agent Cards remain primarily declarative and do not provide the ownership, lifecycle governance or per-instance accountability of a durable IAM principal. A2A should therefore complement the IAM foundation, not substitute for it.
The first step is not a new identity universe for agents.
The first step is simpler:
Put them in IAM.
Classify them clearly.
Govern them before they act.
For a Deeper Dive
For more details on why and how a layered identity model for agents is needed, and how to implement it, read my 5-part series “No AI Agent Without Identity” on HackerNoon:
For broader reflections on agentic AI governance, deterministic control, and the limits of human approval as infrastructure: