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Control evaluation · Practical playbook

Verify AI policy decisions for different teams and roles

A correctly written rule can produce the wrong outcome when the user is mapped to an unexpected group. Evaluate identity resolution, rule scope and membership changes separately before relying on different AI permissions for different teams.

For Identity administrators and AI policy owners

Synthetic example

Fictional sales and finance pilot users

Two dedicated test users require different treatment for a synthetic commercial example. A third account belongs to overlapping pilot groups so the team can inspect precedence without using employee credentials.

What you are working with

  • Dedicated test identities representing each approved team, plus one account with overlapping group membership.
  • A synthetic prompt whose intended action differs between those groups under the documented pilot policy.
  • An identity-to-policy worksheet showing expected membership, applicable rules and the owner of each decision.

A safer approach

  • Use supported identity sources and group features confirmed with the vendor for the current deployment.
  • Make membership changes in isolated pilot groups and preserve a way to restore the original configuration.
  • Record observed propagation time; do not assume changes apply instantly or that all identity attributes are collected.

Expected outcome: Each test account receives the expected policy treatment, and the evaluator can explain overlap, stale membership and identity changes without relying on assumptions.

Put it into practice

Work through the procedure

  1. Map identities to requirements

    Start with business permissions, then map them to the groups or roles the product supports. Record how a user becomes associated with that identity. Distinguish the device's signed-in user from the AI service account so personal and corporate accounts are not accidentally conflated.

  2. Test the clean membership cases

    Run the same synthetic action under each dedicated account after confirming the expected membership. Keep the provider path and device configuration comparable. Capture the outcome in your worksheet and inspect available product evidence for agreement with the intended policy.

  3. Evaluate overlapping rules

    Use the overlap account to observe precedence when more than one policy may apply. Agree the expected result with the policy owner beforehand. If precedence is not documented clearly, ask engineering to explain the supported behavior rather than inferring it from one successful run.

  4. Test a controlled membership change

    Move a pilot identity between agreed groups and repeat the fixture after the documented update process. Record when the new decision appears and whether reauthentication is needed. Restore the test arrangement and note any interval during which the old rule remains effective.

Evidence before approval

What to check before proceeding

1. Identity correctness

Ready when
Each evaluated user is associated with the intended supported identity and policy scope.
If the check fails
Correct onboarding or identity mapping before diagnosing content-detection behavior.

2. Rule precedence

Ready when
Overlapping group membership produces the agreed and explainable outcome.
If the check fails
Simplify overlapping rules or obtain a verified precedence model before deployment.

3. Membership transition

Ready when
A controlled change reaches the intended state within the agreed operational window.
If the check fails
Document the delay and define an interim access procedure for role changes.

Common mistakes to avoid

  • Testing policy differences with two accounts that actually resolve to the same managed identity.
  • Assuming the most restrictive rule always wins without verifying the product's precedence behavior.
Workforce AI Security

Evaluate this workflow with Aona

Where Aona can help

Work with Aona sales and engineering to confirm supported identity integration, group scoping and policy-update behavior for the pilot.

What to confirm

This test does not promise arbitrary identity attributes, instantaneous synchronization or any particular rule-precedence model.

Evaluating a control for your organization?

Bring your target AI tool, device and acceptance criteria. Review the supported control path, the evidence you need and any limitations before deciding on a pilot.

FAQ

Questions about this workflow

Dedicated pilot accounts make expected membership easier to control and avoid changing an employee's access during diagnosis. Confirm that they represent the actual onboarding method.
Technical evaluation

Evaluating a control for your organization?

Bring your target AI tool, device and acceptance criteria. Review the supported control path, the evidence you need and any limitations before deciding on a pilot.

Test AI Policies by Team and Role | Aona AI