They should govern them in the same identity programme, even though the authentication mechanics differ. Devices, services, and IoT assets need inventory, certificate oversight, and clear ownership so trust is not left to ad hoc configuration. If machine identities are excluded, the operational environment remains partially unmanaged.
How teams should treat machine identities in the same identity programme
Human and machine access should not be managed as separate governance universes. The control model can differ, but the programme model should be unified, because both depend on inventory, ownership, assurance, lifecycle discipline, and policy enforcement. A team that excludes machines from identity governance usually discovers the gap only after credentials, certificates, or service accounts have already become operational dependencies.
That said, unification does not mean identical treatment. Human logins usually centre on users, interactive authentication, session control, and recovery workflows, while machine identities often rely on certificates, tokens, workload federation, or other non-interactive authenticators. The practical test is whether the identity can reach production systems or make privileged requests, if so, it belongs in the same governance scope even when its login mechanics are different.
For teams that still separate them organisationally, the better approach is to keep one identity inventory, one ownership model, one review process, and separate technical playbooks for how each population authenticates and rotates access. That is the only way to avoid a split-brain situation where humans are monitored, but devices, services, bots, and IoT assets are effectively trusted by convention.
What machine identity governance must cover that human login governance often misses
Machine identity governance has a different failure surface, because the asset is often embedded in systems, pipelines, or infrastructure rather than tied to a person’s lifecycle. Certificates expire, secrets are copied into build systems, service accounts persist after the original application has changed, and ownership becomes unclear when teams hand off platforms. The governance model has to cover discovery, expiry, rotation, and decommissioning, not just sign-in policy.
Ownership is the practical anchor. Every non-human identity should have a business owner and a technical owner who can answer what it does, what it authenticates to, and what should happen if it fails. Without that, reviews become symbolic, offboarding becomes inconsistent, and the environment accumulates orphaned access paths that no one is willing to revoke.
Inventory is equally important because machine identities are rarely visible through the same channels as people. Teams need a way to find service accounts, API credentials, workload identities, certificates, and shared integrations across cloud, SaaS, on-premises, and embedded environments. Human vs Non-Human Identity is a useful reference point for the governance overlap, while Service Account Security Guide and NHI Authentication Guide show why the control set has to include both lifecycle and authentication patterns.
Where the common failure modes appear in practice
The most common failure is not a lack of policy, it is a mismatch between governance intent and operational reality. Teams write rules for users, but machine identities are created by automation, inherited through templates, or left behind after migration work. The result is long-lived credentials, weak rotation discipline, unclear account ownership, and access paths that survive even when the original use case is gone.
Another recurring issue is overreliance on configuration as a substitute for governance. If a workload can authenticate through a shared secret, a static certificate, or a broadly scoped token, then the environment may appear functional while actually hiding excessive trust. This is where certificate oversight, least privilege, and environment separation matter most, especially for service-to-service access and infrastructure automation. Machine Identity, PKI and Certificate Lifecycle Guide is directly relevant because certificate expiry and renewal are often the point where unmanaged machine identities surface.
Teams also underestimate how much human misuse can creep into machine identity estates. Shared service credentials, manual use of tokens, and ad hoc reuse of the same secret across environments break the separation that identity programmes are supposed to enforce. Top 10 NHI Issues is useful because it frames the operational patterns behind those failures, not just the technical symptoms.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
NIST SP 800-53 Rev 5 sets the technical controls, while ISO/IEC 27001:2022 defines the regulatory obligations.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST SP 800-53 Rev 5 | IA-5 — Authenticator Management | Machine and human access both depend on credential lifecycle and rotation. |
| IA-9 — Service Identification and Authentication | Directly covers service, workload, and other non-human identities authenticating to systems. | |
| AC-2 — Account Management | Identity inventory, ownership, and lifecycle governance are central to this question. | |
| Recommendation — Manage authenticators with defined issuance, rotation, and revocation rules. Enforce service-to-service authentication with unique, managed credentials. Track all human and machine accounts through provisioning, review, and removal. | ||
| ISO/IEC 27001:2022 | A.5.16 — Identity management | Unified identity governance across people and machines fits identity management. |
| A.8.5 — Secure authentication | Machine identities still need controlled authentication mechanisms and secret handling. | |
| Recommendation — Maintain one identity inventory and ownership model across all identity types. Require controlled authentication methods and protect machine credentials carefully. | ||
Practitioner Guidance
What to prioritise: Build one identity governance view for both populations, then apply different authentication and lifecycle controls underneath it. If a machine identity can access production data, deploy code, or trigger privileged actions, it needs ownership, review, and revocation discipline at the same level as a human login.
What to verify: Confirm that every non-human identity has a named owner, a known purpose, a current inventory record, and an explicit expiry or rotation expectation. Also verify that certificates and secrets are not stranded in pipelines, shared stores, or legacy applications where no one can prove who depends on them.
Common mistake: Treating service accounts and certificates as implementation details rather than governed identities. That shortcut usually leaves teams with partial visibility, weak offboarding, and a false sense that “only users are in IAM.”
What good looks like: One programme owns the policy, inventory, and accountability model, while separate technical controls handle human authentication, machine authentication, rotation, and certificate lifecycle. The environment is strongest when no identity, human or machine, can remain both active and unowned.
Practitioner takeaway: Teams should not ask whether machine identities belong in identity governance, they should assume they do and design the programme so unmanaged non-human access cannot exist by default.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on October 7, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org