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Control evaluation · Practical playbook

Verify discovery and enforcement as separate AI capabilities

Knowing that an AI service exists, observing an employee visit and preventing a sensitive submission are separate capabilities. Build a coverage matrix that records each one independently, with the exact account and application path in scope.

For Security evaluators and AI inventory owners

Synthetic example

A small shortlist of fictional employee workflows

An inventory owner selects representative approved AI services for a pilot. For each service, the evaluator separates catalog information, observed use and any vendor-confirmed prompt or attachment control.

What you are working with

  • A shortlist of actual services approved for testing, each paired with a fictional employee task.
  • An evaluator-maintained matrix with distinct catalog, observed-use, prompt-decision and file-decision columns.
  • Synthetic fixtures used only on provider paths the vendor agrees can be evaluated for enforcement.

A safer approach

  • Use dedicated test accounts and only services authorized by the organization for this evaluation.
  • Treat catalog presence as reference information and require separate evidence for usage visibility and action control.
  • Record the exact interface, account type and deployment prerequisites rather than giving a whole provider one blanket checkmark.

Expected outcome: The team receives an honest coverage statement that shows what is known, observed and controlled, including important differences between a broad catalog and a narrower enforcement scope.

Put it into practice

Work through the procedure

  1. Define the matrix columns

    Write a short meaning for each column before testing. Catalog means the service has reference information; observed use means the deployment captures a relevant activity; enforcement means a specified action receives the required decision. Add file redaction only where it is a separately confirmed requirement.

  2. Check inventory and observation

    Look up the approved services and then perform the agreed benign activity using test accounts. Inspect the available usage view after the documented reporting interval. Record what the product actually shows, without assuming it identifies every personal account, embedded feature or native application.

  3. Evaluate supported actions

    On confirmed enforcement paths, submit the synthetic restricted and permitted fixtures. Check prompt and file decisions separately and note any unsupported route. A service appearing in the usage view does not remove the need for this behavioral test.

  4. Publish a bounded coverage statement

    Summarize the matrix using observed, tested, unsupported and unresolved labels. Include versions and prerequisites alongside the result. Give inventory-only services an owner for risk review rather than describing them as protected, and use the matrix to choose the next valuable evaluation.

Evidence before approval

What to check before proceeding

1. Capability separation

Ready when
Catalog, observation and enforcement results remain distinct throughout the matrix and summary.
If the check fails
Split combined checkmarks before using the report for a buying or rollout decision.

2. Action-level evidence

Ready when
Each enforcement claim names the synthetic action, supported path and observed final outcome.
If the check fails
Mark it unverified until a scoped behavioral test establishes the result.

3. Gap ownership

Ready when
Inventory-only or unsupported workflows have a named review owner and an interim handling decision.
If the check fails
Assign responsibility before presenting broad discovery as a complete risk treatment.

Common mistakes to avoid

  • Using a large catalog count as the denominator for claims about prompt blocking or file redaction.
  • Treating a web visit, native application launch and sensitive submission as interchangeable evidence of AI usage control.
Workforce AI Security

Evaluate this workflow with Aona

Where Aona can help

Ask Aona to map its risk catalog, observed usage and currently supported enforcement paths against your specific pilot requirements.

What to confirm

Aona's catalog breadth must not be interpreted as uniform governance across every listed tool; verify provider, interface and release scope separately.

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

Yes. It can support inventory, risk review and policy conversations. Its value should be described accurately without implying that sensitive submissions are prevented.
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.

Verify AI Discovery Versus Enforcement Coverage | Aona AI