They should widen governance to include machine identities and any AI-driven access paths before the volume becomes unmanageable. That means enforcing ownership, limiting standing access, and requiring continuous evidence for creation, use, and retirement so automation does not outpace oversight.
Why This Matters for Security Teams
Automation changes the governance problem from a small set of predictable service accounts to a fast-growing population of machine identities, API keys, tokens, certificates, and now agent-driven access paths. That shift matters because the blast radius of a single missed entitlement expands as systems scale. NHI Mgmt Group notes that NHIs outnumber human identities by 25x to 50x in modern enterprises, and only 5.7% of organisations have full visibility into their service accounts in the Ultimate Guide to NHIs.
Traditional identity programs often assume owners, joiners, movers, and leavers are human-centric events. Automation breaks that model. Identities can be created by CI/CD, infrastructure code, orchestration tools, or AI systems without a clear business owner or retirement trigger. That makes lifecycle governance, evidence collection, and revocation far more important than periodic attestation alone. NIST CSF 2.0 reinforces this operational shift by treating identity governance as part of continuous risk management, not a one-time configuration activity, and the same logic is reflected in the NIST Cybersecurity Framework 2.0.
In practice, many security teams discover identity sprawl only after an audit, a production incident, or a secrets leak has already exposed how much automation escaped oversight.
How It Works in Practice
Organisations should respond by treating every automated workload as an identity that must be owned, justified, monitored, and retired. That starts with inventory: service accounts, workload identities, certificates, tokens, secrets, and any AI agent or workflow that can call tools or access data. The practical goal is to move from implicit trust to explicit evidence, using the identity lifecycle guidance in the Ultimate Guide to NHIs — Lifecycle Processes for Managing NHIs.
Effective programs usually combine four controls:
- Assign a named business or technical owner to each NHI and automated access path.
- Remove standing access where possible and replace it with just-in-time provisioning for specific tasks.
- Use short-lived credentials and rotate or revoke secrets automatically when jobs complete.
- Require evidence for creation, privilege change, and retirement so orphaned identities do not accumulate.
The NIST CSF 2.0 categories for governance, asset management, and access control help structure this work, but the real operational detail comes from tightening the lifecycle: who approved the identity, what it can reach, how long it lives, and what telemetry proves it was used correctly. This is especially important because excessive privilege is common, with NHI Mgmt Group reporting that 97% of NHIs carry excessive privileges in the Ultimate Guide to NHIs.
When automation includes AI agents, governance should also account for the fact that their access paths are dynamic, goal-driven, and hard to predict. Static role design rarely captures that behaviour well, so current guidance suggests pairing workload identity with runtime policy checks rather than relying only on pre-assigned roles. These controls tend to break down when identities are spawned by ephemeral pipelines across many cloud accounts because ownership, logging, and revocation metadata are inconsistent.
Common Variations and Edge Cases
Tighter governance often increases operational overhead, so organisations must balance control strength against deployment speed and developer friction. That tradeoff becomes visible in environments that create thousands of short-lived identities, such as container platforms, serverless systems, and AI orchestration layers where manual review is not practical.
There is no universal standard for this yet, but best practice is evolving toward policy-driven automation, continuous telemetry, and lifecycle evidence. For high-churn environments, a static approval workflow is too slow, while a fully permissive model is too risky. Security teams should favour controls that scale with machine velocity, such as policy-as-code, identity-bound telemetry, and automated offboarding. The broader governance implications are covered in the Ultimate Guide to NHIs — Regulatory and Audit Perspectives, especially where auditors want proof that access did not persist beyond necessity.
Edge cases also appear when third parties create or manage automation on an organisation’s behalf. In those environments, ownership can be fragmented and secrets can live outside sanctioned vaults, which is why the issue pattern highlighted in the Top 10 NHI Issues often becomes a supply chain problem as much as an internal governance problem.
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 address the attack and risk surface, while NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-03 | Identity sprawl demands strict lifecycle and rotation control for machine identities. |
| NIST CSF 2.0 | PR.AC-4 | Expanded automation requires continuous access management and least privilege. |
| NIST AI RMF | AI-driven access paths need governance, accountability, and ongoing risk monitoring. |
Establish ownership, monitoring, and escalation paths for autonomous systems that can request access.
