Security teams should use AI to rank entitlements by risk, peer group fit, and anomaly signals so reviewers spend time on the access that matters most. The goal is not full automation without oversight. A human should still approve decisions, but AI can shrink the review set, reduce rubber stamping, and improve timeliness in large, complex environments.
Why This Matters for Security Teams
AI-assisted access reviews are meant to solve a human scaling problem, but the real risk is letting low-value access become invisible under a flood of attestations. When reviewers face long entitlement lists, they default to rubber-stamping, especially in environments with many service accounts, SaaS integrations, and delegated admin paths. That is exactly where non-human identity (NHI) exposure grows fastest. NHI Management Group’s Ultimate Guide to NHIs frames this as a lifecycle issue, not a one-time audit issue, and the OWASP Non-Human Identity Top 10 reinforces that weak visibility and poor entitlement hygiene are recurring causes of failure. Used well, AI can reduce certification fatigue by ranking access that is most likely to be excessive, unused, or high impact. Used poorly, it becomes another layer of false confidence. In practice, many security teams encounter serious over-privilege only after an access review cycle has already been completed and signed off.
