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Choose an identity and access management (IAM) platform for AI agents by testing whether it can give each agent a distinct identity, constrain what that identity can do, preserve who authorized its actions, and support the agent through its full lifecycle. Start with the workflows your agents will perform—not a vendor’s “AI agent” label—and test interactive, user-delegated agents separately from autonomous agents acting under their own identities.
Why do AI agents need dedicated identity and access controls?
An agent that can access data, call tools, or act across applications exercises authority, even when a person configured or launched it. If it uses a person’s reusable credentials, it becomes harder to distinguish the agent’s actions from the person’s and to determine who was accountable. NIST also warns that long-lived API keys and bearer tokens can be used by anyone who obtains them and may grant overly broad access.
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For selection purposes, treat identity and authority as related but separate questions: What principal is acting? and What is that principal allowed to do, on whose authority, and under what limits? NIST’s NCCoE work identifies agent identification, authorization, delegated access, activity logging, and data-flow tracking as areas to address. A platform that only registers an agent but cannot govern its permissions and actions leaves important parts of the problem unresolved.
Which agent access pattern does your platform need to support?
Decide whether each workflow is interactive, autonomous, or a mix. These patterns have different authority models; a single generic “agent identity” feature does not establish that a platform handles both safely.
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| Pattern | Whose identity or authority is used? | What to verify |
|---|---|---|
| Interactive, user-delegated agent | The agent acts for a signed-in user, using delegated permissions. | Can it receive only the authority needed for the user’s task, without being handed the user’s reusable credentials? Can administrators trace actions back to both the agent and the authorizing user? |
| Autonomous agent | The agent authenticates under its own identity and receives permissions attached to that identity. | Can its access be scoped to its tasks and resources, independently reviewed, limited by policy, and withdrawn without disabling an unrelated human account? |
Microsoft documents these as two examples: delegated, on-behalf-of access for interactive agents and a client-credentials flow using an agent identity for autonomous agents. That documentation illustrates patterns; it is not a universal standard or an independent product comparison. Your design may require both, but identify the pattern for each workflow before evaluating a platform.
What should an AI-agent IAM platform support?
1. Agent inventory, ownership, and lifecycle
Check whether administrators can discover or register agents, give them unambiguous names, assign accountable owners, distinguish them from people and ordinary application workloads, and retire them when they are no longer needed. Ask how the platform surfaces stale, ownerless, or overprivileged agents and supports periodic permission review and deprovisioning. Microsoft describes uncontrolled growth without adequate visibility, management, or lifecycle controls as “agent sprawl”; assess it as a governance risk in your own pilot.
2. Workload identity and credential handling
Establish how the agent runtime proves its identity to the services it calls. Check fit with your workload identity approach, federation model, and runtime environment, and ask how credentials are issued, protected, expired or rotated, and revoked. NIST identifies OAuth 2.0 and SPIFFE among relevant foundations and describes emerging WIMSE work as building on existing protocols. The NCCoE concept paper also discusses OIDC and SPIFFE/SPIRE. Match the platform to the standards and operational maturity your organization is prepared to support; do not treat every emerging draft or proposal as production-ready.
A static API key is not automatically equivalent to workload identity. Ask vendors to show how secrets are kept out of configuration files, markdown files, logs, and other places where an unintended party could obtain them, and how access is stopped when a credential or agent must be withdrawn.
3. Delegation, policy, and least privilege
For user-delegated workflows, check whether the agent receives only the user authority required for the task. For autonomous workflows, check whether policy attaches to the agent’s own identity and limits its actions. In either case, ask whether authorization can be constrained by resource, action, context, or task; whether permissions can be reviewed and withdrawn; and whether approval is required for the actions that genuinely need it. NIST cautions against overly broad access and overreliance on human-in-the-loop approval. These are buyer evaluation criteria derived from that guidance, not a NIST certification checklist.
4. Accountability, logs, and investigation
Determine what an investigator can reconstruct after an incident. Look for evidence that connects an action to the agent identity and preserves the chain to the person or system that authorized it. Ask what is recorded about tool calls, data access, policy decisions, and denied actions, and whether relevant logs can be exported to your existing monitoring and audit systems. NCCoE identifies logging and transparency as areas of interest and says agent actions should be linked to the nonhuman entity.
5. Integration and interoperability
Map the systems each agent actually touches: identity provider, cloud and runtime, APIs, SaaS applications, orchestration layer, and tool interfaces. Verify those integrations directly rather than relying on a broad compatibility claim.
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6. Governance and operating fit
Compare ownership and administration, lifecycle workflows, approval paths, incident response, reporting, and policy maintenance. Consider whether the platform fits your existing identity operations or creates a separate control plane that your team must staff. Available guidance identifies these governance needs but does not establish neutral product-by-product operating costs or rollout effort, so assess those in your environment.
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How should you compare platform options?
At minimum, compare your existing enterprise IAM control plane with any specialist agent-identity or authorization offering under consideration. The available guidance does not establish a market-wide winner or show that one category always fits. Apply the same criteria to every shortlist option:
| Comparison axis | Evidence to request |
|---|---|
| Distinct identity and lifecycle | A demonstration of agent registration or discovery, ownership, inventory, review, and retirement. |
| Delegated and autonomous authorization | Separate demonstrations for a user-delegated task and an autonomous task, including the authority each receives. |
| Workload authentication and credentials | The runtime identity flow and how credentials are issued, protected, expired or rotated, and revoked. |
| Policy and revocation | Examples of permissions constrained to resources and actions, plus the process for changing or withdrawing them. |
| Attribution and audit evidence | A trace from authorizing person or system through agent identity to downstream action, including denials where available. |
| Interoperability and operating fit | Working integrations with your identity, runtime, applications, policy, and logging systems, along with the administration those integrations require. |
Microsoft Entra is one commercial example whose documentation describes agent identities, interactive and autonomous patterns, and workload identity capabilities. Evaluate it against the same requirements as other candidates. The consulted evidence does not establish independent testing, comparative superiority, pricing, or region-specific availability.
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Use representative workflows and require the vendor to show each answer in the product and in the resulting records—not just in a presentation.
- Can the platform represent an agent as a distinct principal and show who owns it?
- Can a user delegate limited access to an interactive agent without giving it the user’s reusable credentials?
- Can an autonomous agent use its own identity with permissions constrained to its task?
- How does the runtime obtain credentials, and how are they protected, expired, rotated if applicable, and revoked?
- Can an administrator follow authorization from the person or system that grants it, through the agent identity, to downstream actions?
- Can the platform identify stale, unowned, or overprivileged agents and support review or deprovisioning?
- Which parts work with your existing OAuth/OIDC, workload identity, policy, logging, cloud, application, and tool systems?
These questions translate NIST and NCCoE concerns into a buyer exercise; they are not a NIST certification checklist.
How mature is the guidance—and what does it establish?
NIST’s agent-identity work is evolving. As of the cited 2026 materials, NCCoE describes its practice guide as planned work, not a completed vendor benchmark. Its project resource hub reports more than 600 responses to its February 2026 concept paper; that figure indicates engagement with the project, not a product endorsement or proof that a particular implementation meets your requirements.
Bill Fisher and Ryan Galluzzo, NIST/NCCoE authors, wrote on August 27, 2026: “The established IAM standards and best practices of today are the foundation upon which we will build the secure and scalable agentic protocols of the future.” Treat established foundations as relevant to the selection, while validating newer protocols and each vendor’s actual implementation in your target architecture.
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