30 Days Gen AI Risk Trial -Start Now
Skip to main content
Policy in practice · Practical playbook

Recheck an AI tool after a vendor change

An AI approval reflects a particular product and set of assumptions at a point in time. A vendor change may leave that decision intact or undermine a condition it relied on. Review the difference that matters to your workflow instead of restarting every assessment or ignoring the notice entirely.

For Vendor risk reviewers, application owners and procurement teams

Synthetic example

An approved assistant adds connected-data features

A service used for public research introduces a new way to connect internal files. Employees interpret the familiar application name as permission to enable the feature without another review.

What you are working with

  • The dated approval record and its permitted use.
  • The vendor's current notice or documentation describing the change.
  • The accounts, settings and tasks that could be affected.

A safer approach

  • Compare the change with the assumptions behind approval.
  • Review new permissions and data flows as separate questions.
  • Communicate an interim boundary while the owner verifies the impact.

Expected outcome: The tool's status reflects the changed workflow, with a recorded rationale for continuing, restricting or reassessing its use.

Put it into practice

Work through the procedure

  1. Capture the change from its primary source

    Save the vendor notice or documentation reference with its date and affected product. Distinguish an announced capability from one enabled in the organization's account. A social post or a new brand name can prompt review, but it does not establish changed contractual or technical behavior.

  2. Compare against approval conditions

    Identify whether the change touches the permitted data, account arrangement, processing location, connected permissions or administrative control. Ask the original decision owner where possible. If the approval has no recorded assumptions, document the missing evidence rather than declaring the change immaterial.

  3. Set and communicate an interim decision

    Keep unaffected approved work distinguishable from the changed feature. Assign any provider-setting changes to authorized administrators and give users a clear alternative. If the impact cannot yet be established, state what remains under review and when the owner will next update the decision.

  4. Verify and update the operating record

    Check current settings, applicable terms and representative task behavior before closing the assessment. Update the register and employee instructions with the revised scope. Retain the reason for the decision so the next change can be compared against an accurate baseline.

Evidence before approval

What to check before proceeding

1. The change is identified precisely

Ready when
The record names the product, source, date and affected capability or condition.
If the check fails
Obtain primary evidence before rewriting approval on rumor alone.

2. Approval assumptions have been compared

Ready when
The owner explains which conditions changed and which remained valid.
If the check fails
Reconstruct the affected part of the assessment before closing review.

3. The operating instructions reflect the outcome

Ready when
Users and administrators can distinguish the permitted and restricted workflows.
If the check fails
Publish the scoped decision and verify necessary configuration changes.

Common mistakes to avoid

  • Treating an existing tool approval as automatic approval for every new connector or feature.
  • Assuming a vendor acquisition necessarily changes data processing, or that unchanged branding proves nothing has changed.
Workforce AI Security

Evaluate this workflow with Aona

Where Aona can help

Aona's supported usage information can help identify which workflows need attention after a change. Supported prompt and file controls may reinforce an interim data boundary where the affected route is covered and tested.

What to confirm

Do not assume Aona automatically reviews vendor notices, contract changes or newly introduced features. The provider's evidence and the organization's assessment determine whether earlier approval remains suitable.

Turning this policy into an operational rollout?

Discuss the teams, devices and AI tools in scope, who will own the policy, and which deployment and evidence requirements need to be met before rollout.

FAQ

Questions about this workflow

Use the original approval conditions to focus the review. A change that affects a key data or permission assumption needs attention; an unrelated feature may not. Record why the chosen level of review is appropriate.
Technical evaluation

Turning this policy into an operational rollout?

Discuss the teams, devices and AI tools in scope, who will own the policy, and which deployment and evidence requirements need to be met before rollout.

Review AI Tool Risk After Vendor Changes | Aona AI