AI agent authorization and ReBAC: where policy engines fall short

Stateless policy evaluation is a poor fit for agentic authorisation: The model assumes the full decision context is available up front, but AI agents create and consume context during execution. That means access can change after the original policy was compiled, and the control no longer matches the operational reality. The practitioner takeaway is that authorisation design must follow the decision state, not just the request shape.

A question worth separating out:

Q: Should teams use ReBAC instead of policy engines for AI agents?

A: Teams should use ReBAC when access depends on object relationships, team membership, or current context that changes during execution. Policy engines still help for simple stateless checks, but they are not enough when the authorisation problem is relationship-driven. The real choice is between static rules and live decision context.

👉 Read our full editorial: AI agent authorization exposes the limits of policy engines