A salesperson needs a usable answer in the middle of a buyer conversation. A folder of policies rarely provides it. A slogan about responsible AI does not tell the seller whether a particular performance claim is approved.
I would build an AI claims framework around a maintained register of statements, evidence and answers. The register can start in an ordinary shared spreadsheet or document. Its usefulness depends on clear ownership and access to current facts.
Start with a manageable scope
Choose one feature and collect its customer-facing claims. Include the website, standard deck, demo script, proposal language and commonly repeated answers.
Record the exact statement. “Fast proposal creation” and “finish any proposal in five minutes” create different expectations and should not be treated as the same claim.
Prioritize statements that could materially affect a purchase or implementation decision: performance, automated actions, supported inputs, human review and data handling.
Give each claim a complete record
My suggested fields are:
- Claim identifier and exact wording.
- Where the statement appears.
- Product version, workflow and deployment covered.
- Evidence reference, date and factual owner.
- Conditions and limitations.
- Approved customer wording and supporting answer.
- Review status, approver and next review trigger.
The framework should link to the evidence without exposing confidential material to everyone. Access can differ between an approved customer answer and the internal records behind it.
Use statuses that lead to an action
An entry marked “reviewed” may still leave a seller unsure whether it can be used.
I suggest four working statuses: approved for the stated scope, revise before use, awaiting verification, and retired. These are proposed operating choices, not a formal certification scheme.
For a pending entry, name the question, owner and target date. For a retired entry, identify the assets that must be replaced. For an approved entry, make the scope visible beside the wording.
Avoid an overall score that hides an unresolved individual promise.
Write an answer the seller can actually use
Illustrative register entry: The initial statement is “AI completes your account review.” Product confirms that the feature drafts a summary from connected records and leaves decisions to the account owner.
The approved wording might be: “Prepare an account-review draft from connected records, with your team reviewing the summary and deciding next steps.”
A buyer asks, “Does it recommend what we should offer?” The record should answer that exact question using confirmed functionality. If recommendation is planned, identify it as planned and avoid representing it as available.
Attach a short demo note: show the connected sources and the user review. That carries the approved promise into the presentation.
Name responsibilities rather than giving everyone ownership
Product confirms capabilities and release status. Relevant specialists confirm security, privacy and other facts within their expertise. Marketing owns clear customer wording. Sales Enablement makes approved material available and retires outdated versions.
The business should name the person who approves publication and the person who maintains the register. One individual may fill multiple roles in a smaller team, but the responsibilities should still be explicit.
Connect the register to change
Review affected claims when a model, data source, action, deployment setting or evaluation result changes. Also review them when a buyer exposes an ambiguity the team had missed.
A periodic review can catch drift, but it should not be the only trigger. A materially changed feature needs a communication decision when it changes.
Give sellers a clear route for questions outside the register. “I will confirm that for your deployment” is a useful starting answer when paired with a named owner and a real follow-up.
Test the framework with a rehearsal
Ask a seller to find an approved claim, explain its conditions, respond to a follow-up and identify where to escalate an unsupported request.
If that takes too long, simplify the interface while preserving the underlying evidence. A short answer card can sit above a more detailed record.
The finished framework should help Sales make a supported promise and help the company maintain that promise as the product evolves.
Put this into practice
The free guide includes a claim-to-evidence worksheet you can use as a starting point. My AI Claims & Messaging Review develops that record alongside recommended copy, buyer answers and a practical review process.
Download the free Responsible AI Claims & Buyer Trust Check · Explore the AI Claims & Messaging Review
Related reading
- The AI Messaging Gap Between Product, Marketing, and Sales
- How to Audit Your Website and Sales Deck for Risky AI Claims
Can You Prove Your AI Claims? Aligning Marketing, Sales and Product
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