Publishers are quietly cutting six-figure AI licensing deals through Snowflake’s Cortex platform, according Digiday, as the market for enterprise content licensing begins to take shape.

The Washington Post, Associated Press, People Inc., and USA Today Network are just three of 17 publishers that have signed on to Cortex Knowledge Extensions, Snowflake’s product for connecting locked-down publisher content to enterprise AI tools via retrieval-augmented generation (RAG). Instead of scraping or exposing raw feeds, publishers can let enterprises query their paywalled or proprietary content inside Snowflake’s AI environment — and get paid for it.

Ben Srour, principal product manager at Snowflake, told Digiday the deals are real and structured in ways that make them easier for enterprises to sign. Contracts are either flat-fee licenses or usage-based, and often paid out of an enterprise customer’s existing multi-year spending commitment to Snowflake, so there’s no new procurement line required.

“You cannot scrape the data—you can’t steal it and use it for model training,” he said. “So that’s why the product has really resonated with publishers.”

Snowflake is not alone in the space. The Financial Times and The Economist have previously signaled interest in RAG royalties from opening their archives to private LLMs. AP’s chief revenue officer, Kristin Heitmann, has said the Snowflake exchange opens “unlimited use cases” covering finance companies, supply chain monitoring, crisis management, and regulatory awareness.

Snowflake’s pitch to publishers includes a point that stands out: it doesn’t take a cut of licensing deals. Snowflake makes money through storage and compute when AI queries run inside its environment. Publishers and enterprise buyers negotiate terms directly.

Snowflake also recently committed $6 billion over five years to Amazon Web Services for custom chips and AI infrastructure, a signal of how much the company is betting on AI workloads.

Not everyone is celebratory. A report from the Open Markets Institute published in April warned that AI licensing marketplaces—where AI companies pay publishers for access to articles, archives, and data—risk repeating the power imbalances of the platform era, citing the take rates platforms charge. Snowflake’s no-revenue-share model is a direct counter to that criticism.

On the enterprise side, the keenest adopters so far are financial services and marketing or communications teams already deep into building AI tools on their own data and looking for trusted external signals to plug in. Most other enterprises are still getting internal AI models and data governance in order before leaning into paid publisher content, Srour said.

Snowflake is designing Cortex for where it believes AI is going: away from chatbots and toward always-on agents quietly working in the background.

“A year ago we were talking a lot about chatbots… but very quickly things are moving into this, like, agentic, automated world,” Srour said. “What do they need? They need data. They need context. They need to know what’s happening in the world.”

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The Associated Press, founded in the mid-1800s to help New York newspapers share reporting costs, is offering buyouts to an unspecified number of U.S.-based journalists — the latest move in a long-running transformation from wire service to technology data company.

The News Media Guild, which represents AP journalists, said more than 120 staff members received buyout offers on Monday. AP executive editor and senior vice president Julie Pace said the goal is to reduce global headcount by less than 5%, though she acknowledged the cut among U.S. staff would likely exceed that figure depending on how many people accept.

“We’re not a newspaper company and we haven’t been for quite some time,” Pace said.

The numbers back her up. Over the past four years, AP’s newspaper revenue has fallen 25%. Big newspaper publishers, once the organization’s financial foundation, now account for just 10% of income. Gannett and McClatchy both dropped AP in 2024. Lee Enterprises — publisher of The Buffalo News, the St. Louis Post-Dispatch, and the Richmond Times-Dispatch — is now seeking an early exit from a contract due to expire at the end of 2026.

Where the growth is coming from

While the newspaper business contracts, AP’s technology revenue has grown 200% over the same four-year period. Kristin Heitmann, senior vice president and chief revenue officer, put it plainly: “If you can think of a large technology company, they are a customer of ours.”

AP was among the first news organizations to move aggressively into AI deals, agreeing in 2023 to lease part of its text archive to OpenAI. It has since launched on Snowflake Marketplace to license data directly to enterprises, stood up AP Intelligence to sell data to financial and advertising sectors, and last year secured a deal with Google to deliver news through the Gemini chatbot — Google’s first content deal with a news publisher.

Elections data is another growth vector. AP saw a 30% increase in election data customers between the 2020 and 2024 cycles, and last month agreed to sell U.S. elections data to Kalshi, the world’s largest predictions market. ABC, CBS, NBC, and CNN all signed on to the AP elections service last year.

What the restructuring looks like

Beyond the headcount reduction, AP is doubling down on video — it has already doubled the number of U.S. video journalists since 2022 — and deploying rapid-response teams that contribute to major stories regardless of geographic base. The organization says it will maintain a presence in all 50 states.

The union is pushing back. In a statement, the News Media Guild said AP “refuses to offer [staff] appropriate training and tools” and is “flirting with artificial intelligence — ignoring the opportunity to differentiate AP news stories as ones that are and always will be created by human journalists.” The union also said AP declined a request last week to bargain over AI use.

AP did not immediately comment on either claim.

Pace framed the restructuring as a strategic choice made from stability, not distress. “The AP is not in trouble,” she said. “We’re making these changes from a position of strength.”

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Encyclopedia Britannica and its Merriam-Webster subsidiary sued OpenAI in Manhattan federal court on Friday, alleging the company used nearly 100,000 of their articles to train ChatGPT without permission, and then used the chatbot to cannibalize the traffic that encyclopedias depend on to survive.

The complaint, filed in the Southern District of New York, says OpenAI made “near-verbatim” copies of Britannica’s encyclopedia entries, dictionary definitions and reference content to train its GPT large language models. It also accuses OpenAI of trademark infringement—specifically, generating AI “hallucinations” that falsely cite Britannica as a source, implying a permission that was never granted.

OpenAI’s response was the standard playbook: “Our models empower innovation, and are trained on publicly available data and grounded in fair use.”

Britannica isn’t new to this fight. The company sued Perplexity last September over similar allegations—that Perplexity’s answer engine reproduces its content without attribution or compensation. That case is still ongoing. The OpenAI suit extends the same theory to a much larger defendant with much deeper pockets and a far larger user base.

The core grievance goes beyond copyright. Britannica’s complaint frames the harm as a flywheel: OpenAI trains on Britannica’s content, then deploys a product that answers the same questions Britannica’s websites would have answered, diverting users before they ever arrive. It’s the same structural argument publishers have been making about AI search summaries, and it’s why policymakers in Europe and Brazil are exploring statutory licensing as a way to compensate content creators whose work powers AI without delivering any traffic in return.

Britannica requested unspecified monetary damages and an injunction blocking further infringement. The case joins a growing docket of high-stakes AI copyright litigation heading for a reckoning in U.S. courts over whether training on publicly available data constitutes fair use—a question on which the industry, publishers, and regulators are all waiting for an answer.

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The fight over whether AI companies should pay for news is starting to move out of private deal rooms and into policy. According to Poynter, policymakers in Europe, Brazil and other jurisdictions are exploring statutory licensing models that would require payment for the use of publisher content in AI systems.

That matters because the current market is lopsided. A handful of large publishers have negotiated licensing deals with major AI firms, while many smaller outlets are left with lawsuits, opt-out tools and not much leverage. A statutory regime would not end that fight, but it could change the terrain from bespoke negotiations to rules-based compensation.

For publishers, the appeal is obvious. Licensing laws could offer a cleaner route to payment than years of copyright litigation, especially if courts keep moving slowly on training-data disputes. Poynter reported that the European Parliament was set to vote March 10 on a proposal that could open the door to such a framework. An earlier European Parliament press release shows lawmakers were already pressing for stronger protections around copyrighted works used by generative AI.

The broader pressure is not coming from Europe alone. Poynter said Brazil is weighing a draft bill expected in April that could also require payments to publishers. That suggests the compensation debate is widening beyond the U.S. lawsuits that have dominated headlines. It is becoming a policy question about whether AI systems should be allowed to ingest and monetize journalism without a standard payment mechanism.

That does not mean publishers are aligned on the best route. Danielle Coffey, president and CEO of the News Media Alliance, told Poynter, “If we get the right verdicts, we will have a functional marketplace.” That line captures the split in industry strategy. One camp still wants courts to establish leverage first. Another sees statutory licensing as a faster answer to a market that now favors the biggest companies on both sides.

Why this matters for newsrooms

The practical question for newsroom leaders is not just whether they get paid. It is whether payment systems arrive in time to matter.

Publishers are already dealing with two linked problems: AI answers that may reduce referral traffic and AI training practices that may use newsroom work without clear permission. Reuters reported in February that the European Publishers Council filed an EU antitrust complaint over Google AI Overviews, arguing that AI-generated summaries can harm publisher traffic and revenue. Statutory licensing would not solve the traffic problem on its own, but it would at least create a compensation track when traffic leakage and content reuse happen together.

The industry is also becoming more organized. Poynter pointed to the UK’s SPUR coalition and Danish publishers’ legal action against OpenAI as evidence that publishers are moving beyond isolated complaints. The underlying argument is straightforward: if generative AI depends on journalism as input, journalism should not be treated as a free raw material.

What comes next

The obvious caveat is that statutory licensing still has major unanswered questions. There is no settled model yet for who would collect payments, how rates would be set or how money would be distributed among large and small publishers. That is where many legislative ideas go soft.

Still, the significance of this week’s story is that compensation is no longer just a matter of private contracts and courtroom theory. It is turning into a live policy option. If lawmakers push it forward, publishers may gain a more predictable route to payment. If they do not, the market is likely to remain a patchwork: rich publishers cut deals, everyone else waits on judges.

For newsroom executives, this is one to watch closely. The question is no longer whether publishers want payment from AI companies. It is whether governments are ready to build the machinery to force it.

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OpenAI is rolling out advertising in ChatGPT, but the dozens of publishers who signed content licensing deals with the company won’t see a cent of the ad revenue.

The company announced last week that ads will begin appearing for U.S. users on free accounts and the new $8/month ChatGPT Go tier. Paid Pro, Business and Enterprise subscriptions remain ad-free.

The Information reported that OpenAI has already pitched the placements to dozens of advertisers. The model is pay-per-view rather than pay-per-click, with ads appearing below ChatGPT’s responses — not within them.

The contrast with Perplexity is striking. The AI search startup launched its Publishers’ Program in 2024, offering revenue sharing when a publisher’s content is referenced in an ad-supported interaction. Perplexity later expanded this with Comet Plus, which pays publishers for traffic from its AI browser.

OpenAI has made no similar commitment. Publishers including The Atlantic, Vox Media, Axel Springer and others signed licensing deals that give OpenAI access to their content for model training and real-time retrieval. Those deals cover content access — not a share of downstream advertising revenue.

“Ads do not influence the answers ChatGPT gives you,” OpenAI wrote in its announcement. “We keep your conversations with ChatGPT private from advertisers, and we never sell your data.”

The move represents a reversal from CEO Sam Altman’s earlier stance. “Ads plus AI is sort of uniquely unsettling to me,” he said at a Harvard Business School talk in May 2024. “I kind of think of ads as a last resort for us.”

With over 800 million weekly active users, ChatGPT’s free tier represents significant monetization potential. For publishers watching their traffic decline as users get answers without clicking through, the lack of revenue sharing adds insult to injury.

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Google told UK lawmakers on Tuesday that doesn’t believe it should pay publishers to train AI models on content that’s freely available online.

That’s the message Roxanne Carter, a leading Google public affairs executive, delivered during testimony before the Lords Communications and Digital Committee.

“When it comes to training AI models on freely available content that is available on the open web, we do not believe that we should license,” Carter told the committee, according to Press Gazette reporter Charlotte Tobitt.

Carter argued that AI training isn’t about copying content but about analyzing patterns across massive datasets to “produce wholly new content.”

Google is open to paying for archive material, specialized datasets, or content that publishers have specifically opted out of training pools. But the company draws a clear line.

“We don’t believe that we need a licence to train, but we are doing licences for access,” Carter said.

There’s a catch for publishers worried about their search rankings.

Carter said publishers can use Google Extended to opt out of AI training while staying in search results. The tool blocks Google’s Gemini chatbot and Vertex development platform from scraping content.

The problem? Google Extended doesn’t stop content from appearing in AI Overviews. To block that, publishers must opt out of Googlebot entirely, killing their search visibility.

When asked directly about AI Overviews opt-out options, Carter didn’t answer. She cited ongoing discussions with the UK’s Competition and Markets Authority, which recently designated Google’s search products for potential regulation.

“Opting out means opting out of the search engine, then you’ve effectively killed off your business before you’ve started,” UK Culture Secretary Lisa Nandy told the committee later that day.

Nandy also said that current AI licensing deals favor major publishers.

“They don’t necessarily work well for the smaller players,” she said.

Google has struck content deals with The Guardian, Washington Post, Der Spiegel, and other major outlets. The company describes these as payments for “extended display rights and content delivery methods like APIs” rather than licensing agreements.

Nandy called AI Overviews an emerging concern, particularly when summaries “become competitor to the original products.”

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Creative Commons has weighed in on one of the hottest debates in AI content licensing: Should websites charge AI companies to crawl their content?

The nonprofit published its position on pay-to-crawl systems last week. The verdict? Cautious support with major caveats.

Pay-to-crawl refers to technical systems that automate compensation when AI crawlers access web content. Think of it as a toll booth for bots.

Creative Commons sees potential benefits. These systems could help independent publishers generate revenue and manage server costs from heavy AI traffic. They might keep content publicly accessible that would otherwise vanish behind paywalls.

But the organization has serious concerns. Pay-to-crawl systems “could be cynically exploited by rights holders to generate excessive profits, at the expense of human access and without necessarily benefiting the original creators,” the group wrote.

The bigger worry: these systems could morph into something resembling digital rights management, “turning the web from a medium of sharing and remixing into a tightly monitored content delivery channel.”

Creative Commons proposed seven principles for responsible implementation. The highlights: Pay-to-crawl should not become a default setting imposed by web hosts. Systems should allow nuanced controls, not blanket rules. Researchers, nonprofits, and educators must retain access. And these systems should avoid surveillance architectures that track how content gets used downstream.

Why it matters for newsrooms: As publishers negotiate licensing deals with AI companies, pay-to-crawl could become another tool in the monetization toolkit. But poorly designed systems could block legitimate journalism uses like archiving, research, and fair use excerpting.

The organization is inviting feedback on its principles as the technology develops.

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Google has removed dozens of AI-generated videos featuring Disney-owned characters from YouTube after receiving a cease and desist letter from the studio on Wednesday.

The videos included Mickey Mouse, Deadpool, and characters from Star Wars and The Simpsons. Many were created using Veo, Google’s own AI video generation tool, according to Gene Maddaus at Variety.

The timing is notable. Disney sent the letter shortly before announcing a deal to license 200 characters to OpenAI, allowing Sora users to create short AI clips with official permission. The message is clear: unlicensed use will be fought, but licensing deals are on the table.

Disney’s letter included a lengthy list of protected characters from Frozen, Moana, Toy Story, Iron Man, Lilo & Stitch, and Winnie the Pooh. The studio also demanded Google implement safeguards to prevent its AI tools from generating Disney characters and stop using Disney content to train its models.

Google responded carefully. “We have a longstanding and mutually beneficial relationship with Disney, and will continue to engage with them,” the company said in a statement. Google pointed to its existing copyright tools, including Content ID for YouTube.

Why this matters for newsrooms: This is the clearest example yet of the carrot-and-stick approach that major content owners are taking with AI companies. As publishers and media companies evaluate their own AI licensing strategies, Disney’s model offers a template: aggressive enforcement against unauthorized use combined with willingness to strike commercial deals.

The removed videos now redirect to a message: “This video is no longer available due to a copyright claim by Disney.”

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Really Simple Licensing, the open standard that lets publishers define how AI systems can use their content, officially reached version 1.0 on Tuesday with backing from major internet infrastructure companies and more than 1,500 media organizations.

Cloudflare, Akamai, Creative Commons, and the IAB Tech Lab all announced support for RSL 1.0. New publisher endorsements include The Associated Press, Vox Media, USA Today, BuzzFeed, Stack Overflow, The Guardian, and Slate.

The standard builds on the familiar RSS format to give publishers more control than the binary yes/no blocking of robots.txt. RSL 1.0 lets sites specify exactly how their content can be used for AI training, indexing, and search applications.

New features in 1.0 include the ability to allow traditional search indexing while blocking AI search applications. Publishers can also mandate monetary or in-kind contributions from AI systems that use noncommercial content.

“For anyone whose livelihood comes from publishing content online, RSL 1.0 is a no-brainer,” said Doug Leeds, co-CEO of the RSL Collective, in a press release.

The contribution-based licensing option was developed with Creative Commons to protect what the organizations call the “digital commons.” This refers to freely available knowledge and creative work that AI systems train on without compensation.

“By including contribution and attribution options, RSL helps protect the creative and knowledge commons that make the internet valuable to everyone,” said Anna Tumadóttir, CEO of Creative Commons, in the announcement.

Cloudflare plans to let customers include RSL licenses in HTTP 402 payment-required responses. Akamai committed to helping publishers enforce their RSL controls.

RSL represents a growing push by publishers to establish clearer rules for AI training data. The standard offers an alternative to the current patchwork of individual licensing deals between publishers and AI companies.

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