They should extend reviews to the workflows themselves, not just the underlying accounts. That means checking which AI systems are using which credentials, what data they can reach, and whether their access still matches the intended business process. Human-style recertification alone is not enough for autonomous machine access.
Why recertification must expand from accounts to workflows
When identity reviews stop at the account layer, they miss the real control question: whether the AI workflow still has a valid business purpose with the data and privileges it uses. The review should follow the workflow end to end, including the system, the secrets it uses, the datasets it touches, and the actions it can trigger. That is the only way to tell whether access remains proportionate.
This matters because AI workflows often chain multiple permissions into one business process. A model, agent, or automation may have access that looks reasonable in isolation, but becomes excessive once you see the whole path from input to output. Reviewers should therefore assess the workflow as an operational unit, not as a set of unrelated accounts.
For teams building the broader identity picture, NHIMG’s NHI Lifecycle Management Guide is useful because it treats lifecycle, rotation, offboarding, and review as one continuous governance problem. That same lifecycle lens also underpins the Identity Security Programme Guide, which helps teams organise ownership and recertification across human, non-human, and AI-agent identities.
What reviewers should inspect in an AI workflow review
A useful review starts with visibility into what the workflow actually does at runtime. Teams should know which AI systems are using which credentials, what those credentials can reach, and whether the accessible data still matches the intended process. If a workflow can query broader data than the business use case requires, or can invoke actions outside the approved process, the review should not be signed off as routine.
The review should also test whether the workflow depends on long-lived secrets, shared credentials, or unmanaged access paths. Those patterns make periodic recertification weak, because the account may still look legitimate while the workflow has drifted far beyond its original purpose. In practice, this is where ownership and inventory matter most: without a clear owner and a current workflow map, access review becomes a box-ticking exercise.
For organisations extending control coverage, the most relevant standards and guidance are the ones that already treat identity, access, and operational discipline as connected. OWASP Non-Human Identity Top 10 and OWASP Agentic AI Top 10 both highlight the risks that appear when credentials, privilege, and workflow behaviour are reviewed separately instead of together.
How to make workflow-level review operational
The practical shift is to review the workflow definition, not only the account record. That means tying each AI workflow to an owner, a business purpose, an explicit data scope, and a documented set of actions it may take. If any of those elements change, the workflow should re-enter review even if the underlying account has not changed.
Good practice is to recertify the smallest unit that can create business impact. For an AI workflow, that often means checking the orchestration layer, the connected tools, the target systems, and the credentials together. If the workflow’s access cannot be explained in business terms, it is probably over-scoped. If the access can be explained but not evidenced, it is probably under-governed.
External controls can support that operating model. NIST SP 800-63 Digital Identity Guidelines is relevant where assurance and authenticator strength matter, while NIST Cybersecurity Framework 2.0 helps teams connect governance, protection, detection, and recovery around the workflow itself. For cloud-heavy deployments, the CSA Cloud Controls Matrix is also a useful reference point for IAM and operational control design.
Risk and Threat Considerations
When reviews do not cover AI workflows, organisations can miss the most dangerous part of the access path: a legitimate account that now powers a broader or more sensitive automation than intended. That creates exposure through privilege creep, data overreach, and hidden reuse of credentials across multiple systems.
Failure mechanism: The account still passes recertification, but the workflow has changed its inputs, outputs, tool access, or data reach. Because the review never examines the workflow boundary, excessive access persists undetected.
Impact: Sensitive data can be exposed, actions can be triggered outside the intended process, and a compromised workflow can provide a much larger blast radius than the account record suggests.
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 800-63 and CIS Controls v8 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-05 — Overprivileged NHI | AI workflows can retain excess access beyond their business purpose. |
| NHI-07 — Long-Lived Secrets | Workflow recertification must consider persistent credentials used by AI systems. | |
| Recommendation — Review workflow privileges against current business need and remove excess access. Rotate or replace long-lived workflow secrets with shorter-lived credentials. | ||
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | Workflow-level reviews address agent access that exceeds intended authority. |
| Recommendation — Bound agent authority to the minimum access needed for the workflow. | ||
| NIST SP 800-63 | IA-5 — Authenticator Management | AI workflow reviews must account for the credentials that enable access. |
| Recommendation — Manage authenticator lifecycle and revoke credentials no longer justified. | ||
| CIS Controls v8 | CIS-5 — Account Management | Identity reviews for workflows depend on keeping account scope and ownership current. |
| Recommendation — Continuously review account ownership, access, and lifecycle for active workflows. | ||
Practitioner Guidance
What to prioritise: Review the workflow owner, the data it can reach, and the actions it can execute before you review the account itself. If those three elements are not explicit, the recertification is incomplete even if the account is formally approved.
What to verify: Verify that every AI workflow has a current business purpose, a named owner, a defined access boundary, and a traceable set of credentials or delegated permissions. If you cannot show how the workflow’s access maps to the process it supports, treat that as a governance gap rather than a documentation issue.
Practitioner takeaway: Identity review for AI only works when it follows the automation path. Accounts tell you who can authenticate, but workflows tell you what can actually happen.
Related resources from NHI Mgmt Group
- Why do generative AI interfaces change how organisations should approach access reviews and identity workflows?
- Should organisations let AI handle permission changes in identity workflows?
- What should organisations do before allowing AI to draft identity workflows?
- What breaks when organisations rely on data security controls that only cover storage systems and not AI workflows?