No. Humans, service accounts, and tokens may all sit inside identity governance, but they should not share the same approval assumptions. Human review flows rely on managers and business context, while NHI governance needs lifecycle, scope, and entitlement controls that reflect machine behaviour and persistence.
Why This Matters for Security Teams
Using the same policy model for humans and NHIs sounds efficient, but it usually creates the wrong approval logic. Human access is typically episodic and context-rich; machine access is continuous, automated, and far easier to reuse at scale. That difference matters because NHIs outnumber human identities by 25x to 50x in modern enterprises, and NHI Mgmt Group notes that only 5.7% of organisations have full visibility into their service accounts in the Ultimate Guide to NHIs.
Security teams often inherit human-centric workflows like manager approval, periodic recertification, and broad role assignments, then apply them to service accounts, API keys, and tokens. That approach misses the real risk drivers: secret sprawl, excessive privilege, weak rotation, and unclear ownership. Current guidance in NIST Cybersecurity Framework 2.0 still assumes controls should map to risk and asset class, not identity type alone. In practice, many security teams encounter NHI abuse only after a leaked token or overprivileged service account has already been used to move laterally, rather than through intentional policy design.
How It Works in Practice
A better model separates the governance pattern from the identity category. Humans should still use approval and recertification flows tied to job function, manager oversight, and business justification. NHIs need lifecycle controls that reflect machine behaviour: creation with explicit owner, tightly scoped entitlement, short credential lifetime, automated rotation, and revocation on task completion or decommissioning. That is consistent with the lifecycle focus in the Ultimate Guide to NHIs — Lifecycle Processes for Managing NHIs.
Practically, this means policy should ask different questions for each identity type:
- For humans: is access justified by role, training, and manager approval?
- For NHIs: is access tied to a specific workload, secret, or integration?
- For both: is the privilege still necessary, documented, and monitored?
For NHIs, the control plane should emphasise inventory, ownership, secret storage, and revocation discipline. The strongest patterns are zero standing privilege, just-in-time issuance where possible, and separate policies for tokens, certificates, and service accounts. That is especially important because NHI Mgmt Group reports that 80% of identity breaches involved compromised non-human identities such as service accounts and API keys in the Ultimate Guide to NHIs. Standards such as NIST Cybersecurity Framework 2.0 support this risk-based separation rather than a one-size-fits-all policy. These controls tend to break down when legacy automation shares credentials across multiple systems because ownership, scope, and revocation become impossible to prove.
Common Variations and Edge Cases
Tighter identity separation often increases operational overhead, requiring organisations to balance governance clarity against deployment speed. That tradeoff is real, especially in legacy environments where service accounts are embedded in pipelines, applications, and vendor integrations. Best practice is evolving, but current guidance suggests that shared approval models should not become shared privilege models. For example, a human approver may sign off on the business need for a system, while the NHI policy still enforces workload-specific scopes and expiry.
Edge cases include break-glass accounts, third-party integrations, and agentic automation. Break-glass accounts may need exception handling, but exceptions should be time-bound and heavily monitored. Third-party NHIs often require stricter contract, ownership, and revocation controls because they sit outside the internal joiner-mover-leaver process. For agentic systems, the policy model becomes even more dynamic because an autonomous agent may chain tools or request access at runtime, which makes static human-style approvals a poor fit. Where organisations need a deeper governance baseline, the Top 10 NHI Issues and the Ultimate Guide to NHIs — Regulatory and Audit Perspectives provide useful framing for auditability and accountability. The practical rule is simple: share governance principles where sensible, but never assume the same policy mechanics fit both humans and NHIs.
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-01 | Identity-specific governance needs separate controls for human and machine identities. |
| NIST CSF 2.0 | PR.AC-1 | Access management should reflect identity type and business risk, not one shared model. |
| NIST AI RMF | Autonomous and dynamic systems need context-aware governance beyond static approvals. |
Define distinct policy and lifecycle controls for NHIs instead of reusing human approval workflows.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on June 7, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
