They should check whether the platform can revoke access cleanly, preserve attribution, and tie non-human actions back to the human or system that authorised them. If an identity product cannot govern agents and service accounts through the same lifecycle logic as users, it will create blind spots as the identity estate expands.
What an identity platform must prove for AI agents and service accounts
Teams should treat AI agents and service accounts as first-class identities, then test whether the platform can govern them with the same discipline used for people: issuance, policy, revocation, attribution, and auditability. The practical question is not whether the platform stores a secret or issues a token, but whether it can follow the identity from creation to retirement without leaving unmanaged access behind.
That means the platform has to handle delegated authority, lifecycle events, and ownership in a way that survives scale. An agent or service account may be software, but the access problem is still about who authorised it, what it can do, and how quickly that access can be removed when the task, environment, or trust relationship changes.
How to assess lifecycle control, attribution, and revocation
Start with revocation. A platform is weak if access removal is slow, partial, or dependent on manual cleanup across apps, clusters, and vaults. For AI agents, this matters even more because the usable access may be spread across multiple tools and runtime credentials, so clean offboarding and short-lived access are stronger indicators than a good-looking admin console.
Next, test attribution. You want to know whether the platform can preserve a chain from non-human action back to the human owner, the workflow, or the system that approved it. That is the difference between a system that merely authenticates an agent and one that can explain why an action happened, which account initiated it, and which approval or policy decision allowed it.
Finally, look for lifecycle symmetry. If user identities have enrolment, review, suspension, and deprovisioning controls, but agents and service accounts sit in a separate, weaker lane, the platform will not scale safely. A vendor-neutral AI agent identity security buyer’s guide is useful here because it frames evaluation around capabilities rather than branding. For service accounts, the Service Account Security Guide is a practical benchmark for discovery, least privilege, managed identities, rotation, and governance.
What should fail a platform evaluation
Teams should be sceptical of products that manage credentials but cannot govern identity behaviour. If a platform cannot show where an agent was registered, who owns it, how its permissions were approved, and how those permissions expire, it is only solving a fragment of the problem. That fragment may look like access management, but it does not give you accountable control over the identity estate.
Another red flag is hidden human reliance. Some products appear to support automation, yet still depend on shared operator credentials, copy-pasted secrets, or manual exceptions to keep workflows alive. That creates brittle ownership and weak attribution, especially when incidents or misuse need to be traced back to a specific authorisation path. The Agentic AI Identity Guide is relevant when you need to compare identity models, delegation, registration, and retirement for agents that act on behalf of people or systems.
Also test for change at scale. A platform may work for a handful of service accounts but collapse when hundreds of identities need rotation, review, segmentation, or ownership correction. When lifecycle logic does not scale, teams tend to create exceptions, and exceptions become the real control plane. For broader identity governance patterns, the Ultimate Guide to NHIs provides the parent concept for how non-human identities fit into a larger lifecycle model.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 and OWASP Agentic AI Top 10 define the specific risk controls and attack patterns relevant to this topic.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-01 — Improper Offboarding | AI agents and service accounts must be revoked cleanly when no longer needed. |
| NHI-05 — Overprivileged NHI | Platform evaluation must check whether agents and service accounts can be constrained to least privilege. | |
| NHI-07 — Long-Lived Secrets | Lifecycle control is weakened when the platform depends on secrets that persist too long. | |
| Recommendation — Enforce offboarding workflows that remove all access paths when a non-human identity is retired. Limit non-human identities to task-scoped permissions and review exceptions regularly. Prefer short-lived credentials and automate rotation for every non-human identity. | ||
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | The question centers on governing agent authority and preserving attribution. |
| ASI10 — Rogue Agents | Poor lifecycle control can leave agents acting after ownership or approval has changed. | |
| Recommendation — Bind agent actions to explicit policy decisions and the approved principal. Detect and disable agents that operate outside their registered owner or policy. | ||
Practitioner Guidance
What to verify: Ask whether the platform can demonstrate the full chain for each agent or service account: owner, purpose, permission basis, expiry, and revocation path. If any of those fields are missing or only exist in documentation outside the system, treat the control as incomplete.
Decision rule: If the platform cannot govern non-human identities through the same policy logic as users, do not accept it as an identity platform, accept it only as a credential store or directory adjunct. That distinction matters because storage without lifecycle control does not reduce blast radius.
What good looks like: Access is task-scoped, revocable without cross-team manual intervention, and attributable back to a human or system owner. Lifecycle events are visible enough that an operator can answer who approved access, when it should end, and what gets removed when it does.
Common mistake: Evaluating support for agents by asking only whether the product can issue tokens or secrets. Token issuance is easy to demo; consistent retirement, ownership, and auditability are the harder capabilities and the ones that expose operational blind spots.
Practitioner takeaway: Choose the platform that can explain, constrain, and retire non-human access as rigorously as human access, because the real test is not whether an agent can act, but whether the organisation can still govern it after the first deployment.
Related resources from NHI Mgmt Group
- How should security teams govern Active Directory service accounts?
- How should security teams implement zero standing privilege for service accounts and AI agents?
- How should security teams govern AI agents that use service accounts and MCP tools?
- Why do service accounts and AI agents create different identity risk than employees?