Look for evidence that non-human activity is driving access volume, entitlement churn, and policy checks. If those events are more representative of workload than named users, usage-based pricing will usually align better with how the platform is actually consumed.
Why This Matters for Security Teams
Seat-based pricing assumes access is anchored to named people with stable entitlements. Usage-based pricing makes more sense when the dominant cost drivers are API calls, policy evaluations, token issuance, rotation events, or automated service interactions. That is often the case in environments with heavy NHI use, where the workload can be a service account, pipeline, bot, or agent rather than a human. The question is not whether identity matters, but whether the pricing unit matches the control unit.
That distinction matters because non-human identities are frequently the larger population and the higher-risk one. NHIs outnumber human identities by 25x to 50x in modern enterprises, and only 5.7% of organisations have full visibility into their service accounts, according to the Ultimate Guide to NHIs. When access volume, entitlement churn, and secrets activity are what actually consume the platform, per-seat licensing can hide the real unit economics and delay governance decisions.
Security and platform leaders should compare billing metrics to operational telemetry, then test whether each active seat maps to a real decision-maker or merely a proxy for automated use. Current guidance from NIST Cybersecurity Framework 2.0 still points teams toward asset, identity, and access clarity before scaling controls. In practice, many security teams discover that their seat model is already inaccurate only after audit exceptions, overage charges, or uncontrolled service account sprawl have become routine.
How It Works in Practice
A practical decision starts with segmentation. Break identity activity into human users, service accounts, workloads, CI/CD automation, and agents. Then measure which group drives the most authentications, policy checks, credential rotations, and admin actions. If the majority of value is consumed by machine activity, usage-based pricing is usually a better fit because it tracks the true operational load rather than headcount.
For agentic or autonomous workloads, the better question is often whether the platform supports workload identity, JIT credentials, ephemeral secrets, and intent-based authorisation. A modern agent may request access only for a task, then release it immediately after completion. That model aligns poorly with seat licensing because the cost is tied to execution, not occupation. The control design should also distinguish Top 10 NHI Issues such as overprivilege, stale secrets, and weak rotation from ordinary user access patterns.
- Track authentications per workload, not only per user.
- Measure entitlement churn, secret issuance, and policy evaluation volume.
- Separate interactive admin access from machine-to-machine access.
- Test whether pricing scales with execution spikes, batch jobs, or agent retries.
Where identity governance is being used to justify commercial terms, the evidence should come from logs and inventory, not assumption. NHI risk data in the 52 NHI Breaches Analysis reinforces that machine identities are often the operational hotspot, while NIST CSF 2.0 supports using measurable control outcomes to inform governance. These controls tend to break down in highly dynamic CI/CD environments where ephemeral workloads are recreated so quickly that seat counts lag actual consumption by hours or days.
Common Variations and Edge Cases
Tighter usage-based pricing often increases metering and governance overhead, requiring organisations to balance billing precision against operational simplicity. That tradeoff is real, especially when procurement wants predictable subscription costs and engineering wants elastic scale.
Best practice is evolving for environments that blend human, service, and agent activity in the same platform. In those cases, current guidance suggests using hybrid models: keep seats for human admins or reviewers, but shift machine and agent workloads to metered usage where the vendor can measure calls, tokens, sessions, or issued credentials reliably. If the vendor cannot separate those categories cleanly, pricing may still be seat-based by contract even though the platform is consumed like a utility.
Edge cases also include regulated environments where audit evidence matters more than cost alignment. Here, identity governance should be tied to NIST Cybersecurity Framework 2.0 outcomes and internal control requirements, not only commercial efficiency. Where autonomous agents are in scope, the same logic extends to workload identity and runtime policy enforcement, because an agent can change behaviour faster than a seat model can reflect it. That is why a fixed user count can look neat on paper while masking a fast-growing fleet of short-lived secrets and machine sessions.
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 CSA MAESTRO address the attack and risk surface, while NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-03 | Covers rotation and lifecycle issues that drive usage-based NHI consumption. |
| NIST CSF 2.0 | PR.AC-4 | Access control outcomes help distinguish human seats from machine workload use. |
| CSA MAESTRO | Agentic workloads need runtime governance and task-based access decisions. |
Use task-scoped controls for agents so usage-based billing matches execution and policy checks.
