AI agents can request, create, or consume credentials dynamically, which increases identity volume and shortens decision time. That makes static inventory and manual approvals weaker controls because the identity event may complete before a human can review it. The response is to govern issuance, ownership, and retirement at runtime.
How AI agents change the machine identity problem
AI agents do not just consume existing machine identities, they can trigger new ones as part of normal runtime behaviour. That changes the control problem from periodic review to active governance of identity creation, delegation, and retirement. Agentic AI Identity Guide is a useful reference for the lifecycle view, while Ultimate Guide to NHIs frames the broader machine identity estate.
The practical shift is that identity is no longer a static asset list. An agent may request a token, exchange a credential, or spin up an access path only when a task starts, which means the identity event can be brief, high impact, and hard to observe after the fact. In that model, governance has to follow the runtime moment rather than rely on yesterday’s inventory.
This is also why ownership matters more than in many conventional service-account scenarios. If an agent can act on behalf of a user, service, or workflow, someone must be able to answer who approved the authority, who can revoke it, and what condition caused it to be issued. NHI Ownership and Accountability Guide and Human vs Non-Human Identity both support that ownership and boundary question.
Why static inventory and manual approval weaken under agent speed
Static inventories assume identities change slowly enough to be counted, classified, and reviewed in batches. AI agents break that assumption because they can create short-lived credentials, request scoped access, or consume delegated authority in response to a live prompt or tool call. NHI Authentication Guide shows the range of authentication paths agents may use, and AI Agent Authorisation Guide explains why least privilege and per-action decisions are central.
Manual approval weakens for the same reason: the review cycle is usually slower than the identity event. If a human must approve each issuance after the agent has already started work, approval becomes a record of intent rather than a meaningful control. The better control point is the policy that governs issuance before the credential exists, plus the telemetry that records what the agent actually did with it.
That is also where lifecycle and retirement become part of the same control plane. If access is easy to create but hard to expire, the agent leaves behind long-lived material that outlives the task. Service Account Security Guide is relevant here because it stresses discovery, least privilege, rotation, and governance for identities that should not remain permanently powerful.
What runtime governance should actually change
The control objective is not “know every identity eventually,” it is “make every identity event attributable, bounded, and reversible while it is happening.” For AI agents, that means issuance should be tied to task scope, the authority should be narrow, and retirement should be automatic when the task ends or the trust condition changes. Zero Trust for AI Agents is the clearest match for that operating model.
Where agents interact with APIs, tools, or downstream systems, the useful question is not only “who is the identity?” but also “what action is that identity allowed to take right now?” That is why per-action policy and delegated authority matter more than broad standing access. AI Agents vs Agentic AI helps frame the difference between a simple chat flow and a system that can accumulate meaningful authority.
At scale, governance also needs an inventory of decisions, not just an inventory of credentials. Teams need to know which agent got which access, on whose behalf, for what task, and under what expiration condition. Identity Convergence Guide is useful when you are trying to unify that operational picture across human and non-human identity estates.
Risk and Threat Considerations
AI agents increase exposure because they can compress the time between credential creation and abuse. A weak approval workflow, overbroad delegation, or delayed retirement can leave a narrow but highly privileged access path available long enough for misuse, exfiltration, or destructive action. The risk is less about the number of identities alone and more about the combination of speed, autonomy, and authority.
Failure mechanism: The agent requests or mints access faster than a human can review it, or reuses an existing credential beyond the intended task boundary, so standing privilege accumulates and revocation lags behind real usage.
Impact: Organisations can lose the ability to contain blast radius, attribute actions cleanly, or prove that access was appropriate at the moment it was exercised. That increases the chance of unnoticed misuse, oversized permissions, and lingering credentials that remain valuable after the task is complete.
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 address the attack and risk surface, while NIST SP 800-53 Rev 5 sets the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-01 — Improper Offboarding | AI agents can leave behind credentials that outlive the task. |
| NHI-05 — Overprivileged NHI | Dynamic agent access often grows beyond the task boundary. | |
| NHI-07 — Long-Lived Secrets | Short-lived agent tasks still create risk when issued credentials persist too long. | |
| Recommendation — Automate agent credential retirement as soon as the task or trust condition ends. Scope each agent credential to the minimum permissions needed for the specific action. Replace persistent agent secrets with short-lived, task-bounded credentials. | ||
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | Agent authority can expand through delegated or reused credentials. |
| Recommendation — Constrain agent authority to per-action policy decisions and narrow delegated access. | ||
| NIST SP 800-53 Rev 5 | IA-5 — Authenticator Management | Agent credentials need controlled issuance, storage, rotation, and revocation. |
| Recommendation — Manage agent authenticators with defined issuance, rotation, and revocation processes. | ||
Practitioner Guidance
What to prioritise: Treat issuance, ownership, and expiry as the core controls, not as administrative cleanup. If an agent can obtain credentials dynamically, build the approval and policy logic around the task boundary, not around a periodic review calendar.
What to verify: Confirm that every agent-issued or agent-consumed credential has a named owner, a defined purpose, an expiry condition, and a revocation path that works without manual delay. If any of those four fields is missing, the identity is already harder to govern than it should be.
Common mistake: Relying on static inventory reports to prove control over a runtime identity estate. Inventory is still useful, but for agents it is only a lagging indicator unless it is paired with event-driven controls and continuous retirement logic.
Practitioner takeaway: The real pressure from AI agents is not simply more identities, it is more identity events happening inside the decision window. The safer design is to make access short-lived, attributable, and automatically retired when the task or trust condition changes.