The AI Agent Identity Governance Gap Why Traditional IGA Falls Short
AI agent identity governance gives every AI agent a named owner, bounded entitlements, and a revocation path that keeps pace with how its access changes. Traditional identity governance and administration (IGA) can represent an agent as an account. But a review still has little to act on when that agent's entitlements were left out of the inventory.
The gap appears inside a certification campaign. A reviewer finds an account named svc-recon-agent and is asked whether its access remains appropriate. The owner field is blank. The approval record points to the ticket that created the credential, and nothing in the campaign shows what the agent reached last month.
So the reviewer approves it. Approval is the least disruptive choice when rejection might break a production workflow. The campaign closes with a green result that proves very little because the failure began earlier, in the inventory it inherited.
The gap is process, not the data model
IGA platforms can model an agent as an account. The gap lies in the surrounding process: review intervals designed for people, approvers who cannot evaluate the grant, and missing ownership.Discovery comes first
Once an agent is found, it needs a named owner who can approve, defend, or revoke its access.Review frequency is not a universal number
NIST SP 800-53 leaves review frequency for the organization to define. Cadence comes from the organization's risk and control framework, not a universal number.
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