The short answer
Marketers learn to inventory objective claims, link them to evidence, disclose material limits, and avoid implying human or scientific validation that did not happen.
The decision standard is simple: preserve the source, state the limits, and make the next human check obvious. A useful article should reduce uncertainty without pretending that every unknown has been resolved.
What to examine
“AI-powered” does not excuse an unsupported promise. Claims about accuracy, savings, detection, safety, or automation need evidence that matches the product and customer context.
Start with scope. Identify the product, account, audience, jurisdiction, data, and decision involved. Then separate what was directly observed from what a vendor, researcher, regulator, or commentator says. Record dates because AI products, access rules, and prices change quickly.
Testimonials, demonstrations, and generated comparisons can mislead. Qualified legal review may be needed for regulated or high-impact claims.
A practical way to do it
- Underline every measurable or implied outcome in the copy.
- Match each claim to current, representative evidence.
- Add limitations where a reasonable buyer could overgeneralize.
Keep the worksheet or test record with the draft. If another editor cannot reproduce the check from the saved evidence, the article is not ready.
Editorial guardrail
Do not fill a missing fact with a plausible sentence. Mark it as unknown, find a stronger source, narrow the claim, or remove it. Commentary belongs in a clearly labeled paragraph after the reported facts, not inside them.
Primary-source reading list
These are starting points, not automatic support for every sentence. The publishing editor must open each cited page and confirm the claim it supports on the day of review.
Bottom line
Marketers learn to inventory objective claims, link them to evidence, disclose material limits, and avoid implying human or scientific validation that did not happen.