The short answer
Readers can compare case studies and research without mistaking a vendor-selected success story for general proof.
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
The useful workplace story includes the job, baseline, participants, controls, duration, measurement, failure rate, review cost, and who reported the result—not just a percentage in a headline.
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.
Productivity findings can shift work, omit quality, or fail outside the tested group. Record funding, selection, and measurement limits.
A practical way to do it
- Prefer original research or the organization’s full report.
- Extract population, task, baseline, controls, and outcome.
- Note conflicts, missing data, and whether results replicated.
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
Readers can compare case studies and research without mistaking a vendor-selected success story for general proof.