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Agentic AI does not make identity and access management obsolete, but it exposes a mismatch: many systems grant permissions to a person, service account, or broad role, while an agent can act through multiple tools, data sources, and applications as a task changes or passes to another agent. The practical fix is to give each agent an accountable identity and grant it limited, attributable authority that is checked again as the work changes.
Why does agentic AI strain inherited access models?
Traditional permissions attach to an account or role
Conventional access controls commonly decide what a human account, service identity, or role may do. That model can be difficult to interpret when an agent uses an identity with broad standing permissions: a log may show which account made a change without making clear which agent, task, or authorizing person was behind it.
Agents can extend the chain of action
An agent may retrieve information, call tools, change application state, or delegate part of a task to a subagent. As that chain grows, permissions granted for one task can outlive its need or be carried into a different context. The risk is not that every existing IAM control has failed; it is that agent autonomy and scale can magnify longstanding weaknesses in attribution, excessive privilege, and authorization that is not responsive to context.
Should an AI agent use a person’s account?
No. An agent should have a distinct identity and credentials, with an auditable link to the human or system that authorized its deployment. NIST cybersecurity experts have warned that credential sharing weakens accountability; as they put it, “Credential sharing is a bad idea in all contexts.” A shared human login obscures which actor performed an action and makes it harder to revoke or investigate access without disrupting the person’s own account.
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Identity and authority are related but different. Identifying an agent answers which actor is this? Authorization answers may this actor perform this action, on this resource, in this context? A unique identity without task-specific authorization can still have excessive access. Conversely, a policy decision is difficult to audit if it cannot be tied to a distinct agent and the principal that authorized it.
What is the current NIST guidance on agent identity?
NIST’s National Cybersecurity Center of Excellence (NCCoE) published an initial public-draft concept paper on agent identity and authorization on February 5, 2026. Its public comment period closed on April 2, 2026. The paper sought input on identification, strong authentication and key lifecycle management, zero-trust authorization, dynamic policy, least privilege for unpredictable actions, delegation, human-in-the-loop authorization, auditable intent, non-repudiation, and prompt-injection mitigation.
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NCCoE reported receiving more than 600 responses to the concept paper. That is a count of responses, not a measure of agent-related incidents, adoption, or security effectiveness. In its summary of public feedback, NIST says commenters favored contextual authorization at runtime and at the task level, with authority attenuated as work moves through chained agents and subagents. They also raised the management complexity of large numbers of agents performing varied tasks.
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NCCoE’s project hub describes work in progress and a planned SP 1800-series practice guide, expected to include example implementations, architectures, build details, and lessons from laboratory work using commercially available technologies. The hub does not establish that the final guide has been published or that a single implementation has been selected.
How should an organization grant access to an AI agent?
- Create an agent identity. Issue distinct credentials for each agent rather than reusing a person’s login or a broadly privileged shared account. Record the human or system principal that authorized the agent.
- Define the task boundary. Specify the tools, data, and actions needed for the task. Use explicit allow-lists and default-deny policies so that access outside the defined scope is refused rather than assumed.
- Enforce authorization outside the agent runtime. Put the policy decision point in a component isolated from the agent’s execution environment. OWASP AISVS 1.0 control 5.2.5 states: “Verify that the policy decision point for agent authorization is isolated from the agent’s execution environment.”
- Make authority temporary and re-check it. Prefer short-lived or just-in-time permissions where feasible, set a defined maximum duration for privileged access, and expire it automatically. Re-evaluate authorization when the task or its context changes, including when work is delegated.
- Preserve the user’s data permissions. At each retrieval and assembly stage, enforce the requesting user’s authorization context rather than relying only on a service account with broader access. Apply data-classification controls to the information an agent can retrieve or combine.
- Record the chain. Log the agent identity, authorizing principal, requested action, policy decision, resource, delegation lineage, and relevant credential or revocation events. Where systems can capture the agent’s stated intent, connect it to the resulting action so investigators can trace what happened.
These are control patterns, not a guarantee that any one product or architecture will meet every organization’s needs. NIST’s project is examining how existing standards, potentially with extensions or profiles, could provide a foundation.
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When should an agent need human approval?
Approval is most valuable for actions with significant consequences, especially when they change security posture or are difficult to reverse. OWASP’s agentic threat scenario recommends restricting tools to the task, requiring explicit approval for security-relevant configuration or permission changes, and classifying actions by reversibility.
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- Routine, reversible changes: allow only within a defined scope and preserve enough logging to review the action.
- High-impact or hard-to-reverse changes: pause for explicit human approval before changing permissions, security configuration, or infrastructure.
Approval is one safeguard, not a substitute for identity, scoped permissions, policy enforcement, or monitoring. A useful approval gate should identify the proposed action and its target clearly enough for a person to make a meaningful decision.
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How can an organization assess whether its agent access model is adequate?
Use these questions to examine the controls in a deployment rather than relying on product claims alone:
| Control area | Questions to ask |
|---|---|
| Identity and attribution | Can each agent and subagent be identified? Can activity be tied to the human or system that authorized it? |
| Scope and duration | Are permissions limited to specific tools, data, actions, and time windows? Can authority be reduced as a task is delegated? |
| Runtime enforcement | Is authorization re-evaluated when task context changes? Is the policy decision point separated from the agent’s execution environment? |
| Data boundaries | Does retrieval preserve the requesting user’s authorization context? Are default-deny behavior and downstream data-classification controls in place? |
| High-impact actions | Are sensitive writes distinguished from reads, gated by approval where appropriate, and assessed for reversibility? |
| Auditability and lifecycle | Can the organization review actions, intent, delegation lineage, credentials, and revocation events in a verifiable way? |
Why are identity controls only one part of agent security?
Strong identity and authorization reduce the chance that an agent can act beyond its approved scope, but they do not address every way an agent may be misused or manipulated. In joint guidance announced on May 1, 2026, CISA and partner agencies recommended limiting autonomy and broad access, using strong identity management and layered defenses, threat modeling deployments, monitoring continuously, and conducting regular security assessments. These measures complement access controls rather than replace them.
The central design objective is therefore not simply to register every agent. It is to make each action attributable to an identity, bounded by authority appropriate to the current task, and reviewable as the task changes or crosses systems.
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