A customer asks whether your product uses AI. Your sales team says yes. Product explains the feature. Security describes its controls. Then someone asks who approved the use case, what customer information it can access and who is responsible if the answer is wrong.
Those are different questions. A good product demonstration will not answer all of them.
For a B2B business, I would start AI governance with that conversation: can the people responsible for a use case explain how it works, what decisions they have made and where the evidence sits?
Start with one business activity
AI governance can become an enormous topic very quickly. A more manageable starting point is a specific activity: drafting support replies, summarizing sales calls, generating product descriptions or recommending candidates for review.
Describe the activity in ordinary language. “AI assistant” is too broad. “Creates a draft support reply using the customer's ticket and our approved help articles; an agent reviews it before sending” gives a team something concrete to examine.
Add the business purpose, the people affected and the boundary of the work. Does the system suggest an answer, publish it, change a record or trigger an action? Those differences should influence the review.
NIST's AI Risk Management Framework is voluntary guidance for considering trustworthiness in the design, development, use and evaluation of AI systems. It offers a useful reference point; it is not a certification awarded to a business for completing a checklist. Source: NIST AI RMF overview.
Follow the work, rather than just the tool
Illustrative scenario: A software company approves a support assistant for drafting answers. A manager later connects it to account records so agents can answer billing questions.
The tool's name has stayed the same. Its access and the consequences of a poor answer have changed.
I would ask the team to walk through one ticket from beginning to end. What information is retrieved? What appears in the draft? Can the agent inspect the source? Who can send the reply? What happens if the customer challenges it?
That walkthrough may reveal a mismatch between the approved use and the current workflow. It may also confirm that the controls are working. The purpose is to find out, rather than assume either result.
Give someone responsibility for the decision
A named owner should be able to explain the intended use, keep the relevant records current and bring unresolved issues to people with the authority to act.
That does not mean one person performs every task. Product may understand the feature; Security may review access; a privacy specialist may assess data handling; Operations may manage the human review process. Leadership still needs to know who can approve, restrict or pause the use.
An owner's name without decision authority is an incomplete answer. So is a committee that cannot explain who makes the final call.
Ask for a small set of useful records
For an initial review, I would request:
- A description of the actual use case and its owner.
- The approval decision and any conditions attached to it.
- Relevant vendor terms, settings and data-flow information.
- Evidence of testing and the limitations identified.
- Instructions for human review, reporting problems and making changes.
Do not collect material simply to make the folder look complete. Ask which question each record answers. A policy may describe the intended process, while an approval record shows whether that process was followed for this use case.
Where the evidence is missing, record “not yet verified” and assign the follow-up. Avoid turning uncertainty into a confident finding.
Decide what deserves attention first
My starting priorities would include sensitive information, actions that are difficult to reverse, decisions affecting people, and customer claims that the business cannot substantiate.
Use those as discussion prompts, not a universal scoring formula. Context matters. A draft shown to a trained employee is different from a statement sent directly to a customer, even when both use the same model.
A workable first month might produce a scoped inventory, named owners, a review of a few priority uses and a short action plan. It should also identify where technical testing, privacy review or legal advice is needed.
The first useful result is a business that can explain its AI use more clearly and make the next decision with better information.
For the customer communication side of responsible AI, use the free Responsible AI Claims & Buyer Trust Check to review one product promise, or explore the AI Claims & Messaging Review for a focused review of website copy, sales materials and buyer answers.
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