Layoffs in the U.S. and U.K. journalism industry topped 2,300 newsroom jobs in the first half of 2026, Press Gazette reported July 14, a trend that, if it continues, represents an almost 34% increase over all of 2025’s journalism job losses. The majority of jobs lost are among public broadcasters and wire services alongside newspapers, magazines and digital publishers.

The Press Gazette’s running tally, tracked at least 3,434 jobs lost in 2025 and at least 3,875 in 2024.

Publishers increasingly describe the changes as newsroom reorganizations rather than cost-cutting measures, the underlying pressures remain visible. As audiences migrate to video, social platforms and AI-powered search and chat interfaces, news organizations are redirecting resources toward digital products, audience growth and new distribution strategies. 

The BBC has said it plans to eliminate up to 2,000 positions, roughly one in 10 employees, in what would be the broadcaster’s largest workforce reduction in 15 years. BBC News is expected to bear much of the impact as the organization seeks hundreds of millions of pounds in savings. 

In the U.S., NPR is cutting up to 30 newsroom positions while offering buyouts to hundreds of employees as it meets shifting audience habits and the loss of federal subsidies. The Associated Press is also reducing its editorial workforce through a combination of buyouts and layoffs as it shifts investment toward visual journalism and digital products. 

Other publishers have announced smaller but persistent reductions. CBS News cut about 66 employees and has shut down its century-old radio division. The Washington Post is shrinking parts of its newsroom and business operations, while Vox Media, Condé Nast, Future, Politico, Bustle Digital Group, The Standard, and Nexstar Media Group have also reduced their editorial staff this year. 

At the same time, many are expanding their use of AI to automate production workflows, personalize recommendations and support reporting, raising questions about the fate of the traditional newsroom structure as emerging technologies reshape the industry.   

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Meta’s crawlers hit websites 9.1 billion times in the second quarter of 2026 and sent almost nobody back in return. That single figure, pulled from DataDome’s Q2 2026 AI Traffic Report, captures the widening split between the agents that consume publisher infrastructure and the ones that actually deliver readers.

DataDome’s network processed 17.7 billion AI agent requests between April and June, a 45% jump from Q1’s 12.2 billion. The report draws on 5 trillion signals analyzed daily across more than 400 enterprises. Since January, the network has logged over 30 billion AI agent requests in total, and the monthly curve kept climbing: 4.77 billion in April, 6.29 billion in May, 6.60 billion in June.

Meta drove most of that growth. Its two crawlers do different jobs. Meta-ExternalAgent reads websites to train AI models without sending traffic or compensation back to publishers. Meta-WebIndexer works more like Google’s crawler, indexing pages so Meta AI can answer real-time queries. In Q2, ExternalAgent grew 74% to 5.3 billion requests and WebIndexer grew 163% to 3.75 billion. In June, WebIndexer passed ExternalAgent in monthly volume for the first time, a sign Meta is investing in the answering side of AI as much as the training side.

Crawl volume and referral value are pulling apart. ChatGPT-User, the top agent in Q1, fetched pages 6% less often in Q2. Yet OpenAI’s chatbot still commands 80% to 88% of all AI-driven referral traffic and grew referrals 17% quarter over quarter. Among the rest, Claude referrals more than doubled to 876,000, Perplexity grew 37%, and Grok collapsed 74% to just 24,000 visits.

The distinction matters because publishers have spent the past two years arguing that AI companies use their content without returning referral traffic or other value in exchange. That tension runs through the AI scraping economy, and DataDome’s numbers put figures on it.

The report also flags a new signal worth watching: Model Context Protocol traffic. MCP, the connective layer between AI agents and external tools that Anthropic introduced in late 2024, went from negligible volume to peaks near 500,000 requests a day. Most requests come from AI agents taking inventory through calls such as initialize, tools/list and prompts/list. Rather than reading content, those requests reveal what an agent intends to do before it takes action.

For newsrooms and publishers, the practical message is that bot-or-not detection no longer cuts it. Meta-ExternalAgent, Meta-WebIndexer, ChatGPT-User and a chat session all demand different responses. DataDome recommends agent-level classification, MCP monitoring, and identity validation through standards like Web Bot Auth rather than trusting user-agent strings, which are easily spoofed. Any allowlist granting automatic access based on a trusted agent name is exposed.

Already, 54% of DataDome customers have adopted agent trust policies. The firm frames that as a leading indicator. As Q3 data arrives, the open question is whether Meta’s tilt toward real-time indexing holds, and whether publishers can tell the difference between an agent burning their bandwidth and one bringing them an audience.

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OpenAI’s first piece of consumer hardware is reportedly a screenless, mobile AI companion that syncs with ChatGPT and is being pitched internally as a humanlike AI companion that lives in the home.

That description comes from a Bloomberg report published Tuesday, which TechCrunch summarized the same day. The device is still under development, and its sources describe it as something well outside the standard smart-speaker mold.

The speaker reportedly has a personality and can learn about its owner over time to deliver more personalized responses. It would tap into a user’s digital life, pulling from sources like email. And it apparently includes mechanical elements that can move on their own, designed to feel like a companion and act as a physical manifestation of ChatGPT.

OpenAI announced prototypes for hardware in November 2025, with earlier rumors pointing to a phone that would compete directly with Apple. The company also acquired io, the hardware startup co-founded by former Apple design chief Jony Ive, in a deal valued at roughly $6.5 billion. Bloomberg reports the speaker was built with help from ex-Apple engineers who worked on the iPhone and Mac.

That pedigree is now a legal liability. Apple sued OpenAI last week, accusing it of stealing trade secrets and calling the allegations “the tip of the iceberg.” OpenAI denies wrongdoing. Its sources told Bloomberg the new product veers significantly from anything Apple sells today.

OpenAI is not alone in chasing this category. Hark, the AI lab founded by Brett Adcock, raised an oversubscribed $700 million Series A in May at a $6 billion valuation to build proprietary models paired with custom hardware it calls a universal interface between humans and machines. Hark has yet to disclose the device’s design, highlighting the surge of investment flowing into AI hardware long before products ship.

For newsrooms and publishers, a screen-free device that pulls from email and learns a user’s habits raises the same questions as any voice-first platform. If people increasingly ask a companion device for news instead of opening an app or a browser, distribution shifts again, and this time to a surface with no visible headlines, no scannable feed and no obvious place for a byline.

The referral traffic problem publishers already face with chatbots gets sharper when the interface is spoken. The reported device would extend a broader shift in news discovery, making AI assistants an even more prominent intermediary between publishers and their audiences.

OpenAI has not announced the product, its price or when it will ship. Still, the reported device points to the company’s broader strategy of extending ChatGPT beyond screens and into the home.

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Nic Newman stood in front of a slide that read “AI can do what journalists do quicker and better.” It was a deliberately provocative framing, and the Reuters Institute senior research associate used it to make a sharper point about where the threat to publishers is actually heading.

Speaking at the Media Voices Publisher Summit in London on 10 July, Newman warned that AI models’ ability to serve up what he calls “liquid content” in whatever format a reader wants is a really serious challenge for news media, as reported by Press Gazette.

He demonstrated with a live example. Asking Anthropic’s Claude about the recent U.K. heatwaves, Newman got answers in a Q&A format, filterable graphs comparing air conditioning uptake across countries and Met Office warnings pulled together on the fly. The same information base used by news outlets, adapted to a user’s specific needs and context.

“Content is becoming much more fluid, whether we like it or not,” Newman said. “It’s going to be remixed in many different ways, and audiences will expect and like that level of personalisation.”

The worry is not just today’s chatbots. Newman pointed to agentic tools that complete tasks without being asked, such as ChatGPT Pulse, which digests a user’s chat history and connected apps like Google Calendar to deliver a morning brief unprompted. He expects AI to increasingly turn publisher newsletters into convenient audio digests too.

“People not having to put words into a search box, but the AI agents knowing what you’re interested in and bringing it to you automatically” is the shift publishers should fear most, he said.

Newman’s 2026 trends and predictions report, based on responses from 264 news leaders, found publishers see novel content as their way forward. Original investigations and reporting from the ground ranked highest, followed by contextual analysis and community-building through events. General news for everyone, Newman argued, is exactly what AI will commoditise.

He also urged publishers to fold AI into their own products rather than cede the ground entirely. On-site chatbots, like Ask The News, a product The Washington Post has been developing, can pair human curation with AI’s ability to answer specific reader questions.

The second disruption he flagged is the rise of personality-led and creator-style journalism. Citing Financial Times analysis by John Burn-Murdoch, Newman noted social platforms have become less social and more about following individuals. Joe Rogan now reaches roughly a fifth of American adults weekly. Audiences describe creator-led media as more trustworthy and relatable, even as they rate it less impartial overall.

For newsrooms, the takeaway is uncomfortable but clear. The funnel model, built around using newsletters, podcasts and social traffic to bring users back to a website, remains relevant but faces long-term pressure as audiences consume news differently. Younger audiences are moving elsewhere: 52% of 18-to-24-year-olds now name social, video and AI platforms as their main source of news, up from 40% five years ago, according to the latest Digital News Report covered on The Media Copilot.

Newman sees the future in show- and talent-led models built around personalities and niche audiences. Goalhanger, a U.K. podcast producer known for series including The Rest Is History and The Rest Is Politics, is adding written content to their model, while The Guardian’s Guardian Studios is expanding the publisher’s work across branded storytelling and commercial partnerships. The growth opportunity, Newman said, is building habit and trust around personalities and brands, then finding ways to turn that relationship into a lasting business.

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Freelance writers for Take a Break’s Fiction Feast, Bauer Media’s monthly compendium of short stories, have been told their services are no longer required. In their place: stories that appear to be drafted by AI and credited to “The Fiction Feast Team.”

The change was reported by Press Gazette, which says that whole stories now appear to be produced with AI tools rather than commissioned from human authors. Bauer Media has not responded to requests for comment.

Press Gazette’s Dominic Ponsford framed the likely motive as financial. Costs are tight, and cutting freelance commissions may be a way to keep the title running while keeping the remaining named human authors in work. Ponsford presents this as a possibility, not an established fact, and acknowledges he cannot verify the underlying reason.

What makes this case notable is the setting in which the AI is being deployed. Fiction is among the creative forms readers are least likely to embrace when they learn it was generated by AI. That makes a magazine built around human-authored short stories an unusual place to test audience acceptance of synthetic writing, particularly when publishing under a house byline rather than clearly disclosing AI involvement.

The move fits a broader squeeze on paid creative work. The Author’s Guild has repeatedly called for AI-generated works to to be clearly labeled to prevent them from being passed off as human-written and to protect the market for human authors. Publishers introducing AI into creative publications are stepping into that dispute.

The decision comes amid a worsening climate for freelance writers and creative workers. Newsroom and publishing job cuts have accelerated, with the 2026 layoff wave already outpacing the previous year by early spring. Faced with those pressures, publishers may see AI-generated drafts as a way to cut down on freelance spending.

Traffic data in the same Press Gazette briefing shows why money is tight. Most of the top ten U.S. news websites lost more than 20% of their traffic year on year in June, with Substack the lone gainer at 25%. Buzzfeed fell 48% to 46 million monthly visits. Globally, 45 of the biggest news sites saw declines in April 2026 alone. Google’s expansion of AI Overviews and AI Mode in its home market is a major driver of those drops.

For newsrooms and publishers, the Take a Break decision offers an early look at a challenge more titles may soon confront. When search referrals fall and budgets shrink, the temptation to replace paid contributors with AI grows, and fiction is no longer off-limits. The open questions are whether readers notice, whether they care, and whether a house byline like “The Fiction Feast Team” counts as adequate disclosure.

Bauer has not addressed those questions publicly. The outcome could shape how other publishers think about AI in creative work: if readers see little distinction between commissioned fiction and AI-generated stories, publishers may feel more comfortable expanding such experiments. If readers object, the episode could underscore the reputational risks of introducing AI into publications built on human authorship.

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Germany has become the first country to explicitly classify AI search features, such as Google’s AI Overviews and Perplexity’s answers, as media products subject to national media law, according to Reuters. 

The country’s Commission for Licensing and Supervision, which represents Germany’s 14 state media authorities, has argued that AI summaries and chatbot answers go beyond aggregating existing information as they create new outputs that reflect the providers’ own systems. 

This follows a separate June 2026 court case in which a Munich court found Google could be held directly liable for inaccurate information produced by its AI Overview feature, according to the German newspaper publishers’ association BDZV.

Germany’s media regulator said AI search tools fall outside the European Union’s usual platform liability protections because they are not merely hosting third-party content but curating their own responses. The regulator also said Google’s AI Overviews and Perplexity’s chatbot answers can shape what news audiences see, raising concerns about publishers’ visibility and reach.  

As a result, the services provided by AI search features are therefore subject to German regulations aimed at protecting media plurality.

The decision could give regulators and publishers worldwide a new foothold in their push to hold AI companies accountable for how generated answers reshape the news ecosystem. It also weakens one of the key defenses used by technology platforms, which claim only to be intermediaries organizing information created by others. 

The case may also become a blueprint for other European regulators, which have intensified investigations into major technology companies over competition, privacy and online safety concerns in recent years. 

Google intends to appeal the decision, with a spokesperson characterizing the classification as a failure “to recognize how people’s preferences when searching for information and the information ecosystem are changing.”

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The Associated Press has joined SPUR as the coalition’s first U.S. founding member, adding one of the world’s largest news licensing organizations to a publisher-led effort to create standards for how AI companies track, value and compensate journalism.

Founded in March 2026, the Standards for Publisher Usage Rights is a publisher-led coalition aiming to move AI content use away from opaque scraping and toward a usage-based licensing model where publishers can see how their work is accessed and used. Its founding members include the BBC, the Financial Times, The Guardian, Sky, The Times of London and European group MediaHaus. The AP now joins 30 publisher members and six affiliates.

SPUR’s central argument is that publishers need more than the ability to block AI crawlers. They need visibility into what happens after AI systems access their content.

SPUR’s technical foundation is a content telemetry standard announced June 12 and open for public comment through July 24. The framework breaks AI content use into five measurable events: content retrieved, grounded, cited, displayed and engaged. It creates a common format for reporting those interactions back to publishers.

The standard also defines the underlying data schema, allowing publishers, platforms and vendors to integrate with the same system.

SPUR has begun testing the framework beyond its membership. Microsoft and CDN provider Fastly participated in a recent London public comment event, while licensing and infrastructure startups including TollBit, Redpine and MonetizationOS have said they plan to implement the standard.

The effort differs from earlier publisher initiatives because it focuses on measuring usage after content enters AI systems. The IAB Tech Lab‘s Content Monetization Protocols, by contrast, focused more heavily on pre-crawl access controls and bot management.

But adoption remains the biggest challenge. SPUR can define how AI usage should be measured, but it cannot force AI companies to provide that information. No single publisher has enough leverage to compel companies such as OpenAI or Google to adopt publisher-friendly standards.

SPUR’s strategy is collective action. If enough publishers adopt the same framework, they may create enough pressure for AI companies to participate. That collective-action logic echoes other recent moves, from Reuters and Time shifting to bot-blocking whitelists to broader efforts to build a global publisher alliance.

“The key here lies in both parts of this being a collective action,” Scott Messer of Messer Media told Digiday in an email. “A divided set of publishers cannot battle the forces of LLMs.”

The approach reflects a broader shift in the publisher-AI debate. Instead of focusing only on payment, SPUR members are trying to establish permission and transparency as the foundation for future licensing.

Publisher alliances, however, have a complicated history. During the rise of programmatic advertising, shared industry systems often created value for platforms while leaving publishers with limited control.

Alessandro De Zanche, a former News U.K. executive and founder of media strategy consultancy ADZ Strategies, argues SPUR differs because publishers are approaching AI through the lens of content ownership rather than advertising inventory.

“The teams that drove the advertising channel into a wall are not the ones now dealing with content, IP and LLMs,” De Zanche said.

With AI, he said, publishers are not selling volume. They are selling accuracy, provenance and reliability, and the stakes are “completely different.”

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The growing popularity of AI chatbots is reshaping how audiences discover news, with one in 10 people worldwide now using tools such as ChatGPT, Perplexity and Google’s AI Overviews for news at least weekly, according to the Reuters Institute for the Study of Journalism’s Digital News Report 2026. 

On July 13, Arc XP, a media operating system developed by the Washington Post, launched Ask The News, an AI-powered conversational search tool that publishers can embed on their own sites. Users can ask questions of Ask The News, which answers using the publisher’s reporting with attribution and editorial safeguards. The tool will decline to answer questions when it does not have enough source reporting to generate a confident response, Arc XP says, rather than hallucinate an answer. 

Arc XP’s Subscription Gateway, a capability embedded into Ask The News, changes the traditional paywall model by limiting AI-generated answers rather than articles, prompting readers to subscribe after they have received value from the tool.

For newsrooms, the tool could offer a new way to understand audience demand. Instead of relying on clicks and page views, Ask The News allows publishers to see what questions readers have and subsequently use those insights to guide coverage decisions. 

“Search shows links. Generic AI gives answers from the open web,” said Joey Marburger, Vice President of Content Intelligence, Arc XP. “Ask The News answers with a publisher’s journalism, rules, and business model. This is about building a durable reader habit: when you have a question, you go to your trusted news organization first.”

As AI-generated answers become an increasingly common way for people to access information, publishers may be forced to rethink how their reporting reaches audiences through emerging AI experiences in addition to through traditional means. 

Ask The News is now available to Arc XP publisher partners with a JavaScript embed option for non-Arc XP publishers. Arc XP plans to expand the tool with features including personalized briefings, saved conversations, topic tracking and editorial intelligence dashboards. 

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Speed has always been oxygen in the news business, and the 2010s gave newsrooms an extra reason to breathe deeply. When search and social were the main pipes to readers, the pressure to publish first was constant. Especially around major live events like the Oscars or the Super Bowl, the pressure to post fast often meant preparing “shell” stories in advance, with potential headlines and background information already included.

I’ve made this point before: AI has a tough time with breaking news. Because it takes time for facts to be verified and a consensus to emerge about what happened, AI systems—and in particular Google—tend to shy away from summarizing events in the early minutes or hours of a news event. You would think, then, that speed is a diminishing asset in an AI-mediated news environment.

The reality is messier. Some news publishers are pushing in the opposite direction, opting to publish faster, and with more stories, in the wake of breaking news. For its World Cup coverage, USA Today prepared several shell articles around major games, as Digiday reported. Internal AI systems helped accelerate that process, with human editors altering and publishing them as the games developed. USA Today had already tested the approach during the Winter Olympics and got enough of a lift to run the same playbook, at greater scale, at the World Cup.

Getting into the citation pool early

Fast-turn news isn’t the innovation here. The AI layer is. It’s unclear how long it takes for Google to create an AI Overview around a breaking topic. The Digiday piece cites one test in which AI Mode had access to a breaking story’s information within 10 minutes. AI Overviews appear to move more slowly: One SEO consultant said he had seen them appear within about four hours, and sometimes as long as half a day, while acknowledging there isn’t a lot of good data to go on.

Google may need hours to formulate an AI Overview, but USA Today’s results suggest early publication still pays. Being part of the initial set of sources that compose the answer bestows an advantage for ongoing inclusion—as long as the engine treats you as authoritative and the piece maps to the queries readers are actually typing into AI search.

This is why treating shell articles as an ongoing strategy, rather than a one-off, matters. Having multiple stories around the same topic, linking to each other, is a strong signal. It doesn’t hurt that USA Today is a major domain. There’s also a reporting factor at work: USA Today reporters are physically at the games, gathering exclusive quotes, facts, and perspectives in the follow-up. AI sees all of that and notes the pattern as it considers what to include in a summary.

So is there a first-mover advantage? The evidence is mixed. Being early to a story likely factors into inclusion. Muck Rack analyzed more than one million links cited by major AI systems and found that the highest citation rate occurred during the first seven days after publication. Recency shapes what gets picked, but the first article to hit publish doesn’t automatically beat the fifth.

The takeaway for AI: early counts more than first. And speed is only one input. Established authority—either on a topic or in the news media broadly—is clearly an advantage. A study from SEO tools company SE Ranking that analyzed 75,550 AI Overviews found that, among recognized news outlets, 10 publications received almost 80% of all mentions. The BBC, The New York Times, and CNN alone accounted for 31%.

The unit of competition has changed

The deeper shift is that the ranked link is no longer the unit newsrooms are competing over. Search rankings still matter, but they are increasingly feeding something else: a cluster of sources that an AI system uses to compose an answer. In that world, ranking is a means. Being one of the sources the answer can’t leave out is the actual goal.

The prize isn’t only the click anymore. It’s presence, citation, and narrative authority, the chance to help set the terms of the story before the reader ever lands on a publisher’s site.

That reshapes the newsroom playbook without discarding it. The job is to prepare for predictable uncertainty: map the outcomes you can foresee, the questions readers are likely to ask, and the context an AI system will need to grasp why the event matters. Before news events, consult with your team and AI on possible outcomes, the stories you’d create, and the search queries that people are most likely to ask. Choose the stories you want to be authoritative on, and use AI to help prepare shells and ensure that all your staff is trained up to know what to do.

The trap to avoid is publishing an empty container with a headline and a promise of updates. The winning article is fast, but not thin. It answers the obvious question, supplies the necessary context, links to relevant background, and shows evidence that someone is actually reporting the story. That means writing for two audiences in a single draft: the human who wants the latest developments, and the machine deciding which sources belong in the answer. Background, links, metadata, original quotes, clear sourcing, and visible updates all become part of the same authority signal.

Reporting is still the moat

Then push that authority beyond the first article, not by spraying the same story everywhere but by reinforcing the reporting where readers and AI systems already go to confirm it. The follow-up analysis can become a short video, a podcast segment, a newsletter item, or a social post, and the goal is consistency, not duplication. AI is a great accelerant, but not a replacement for reporters or reporting.

The metrics also have to catch up. Clicks still matter, but they will undercount the value of this work. Newsrooms need to know whether they’re present in AI answers, whether their reporting is showing up (and how prominently), and whether their original facts and framing are making it into the summary. Traffic share is only half the picture. Share of the answer is the other half.

The tactics are there for publishers with the actual reporting to back them up. Speed still creates the opening. Authority determines who owns the answer—and whether winning it is worth anything.

A version of this column appears in Fast Company.

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The New York Times and a group of other publishers are asking a federal court to sanction OpenAI, accusing the company of withholding or destroying evidence in a high-stakes copyright case over how ChatGPT was trained and used.

In a motion filed Thursday in federal court in Manhattan, the publishers alleged that OpenAI misrepresented its ability to search training datasets and ChatGPT output logs for copyrighted news material. According to Reuters, the publishers said OpenAI told the court it could not search its large language models for their work while allegedly concealing that it had already done so “even before the first News Plaintiff filed suit.”

The motion is the latest escalation in the copyright fight between major news organizations and AI companies. It also moves the dispute deeper into discovery, where the question is not just whether AI companies can use journalism to train models, but whether they can preserve, search and produce the records needed to prove what happened.

The plaintiffs include The Times, the New York Daily News and other media organizations, including Ziff Davis and the Center for Investigative Reporting, according to The Associated Press and Variety. The original New York Times article reported that the publishers are seeking legal sanctions against OpenAI, including monetary penalties and other remedies.

The filing does not ask for sanctions against Microsoft, which is also a defendant in The Times’ broader copyright case, according to The Times’ summary of the motion. Microsoft has invested heavily in OpenAI and integrated OpenAI technology into products including Copilot.

“The evidence is in OpenAI’s training data sets and ChatGPT output logs,” the publishers said in the motion, according to The Times. “But instead of just producing that evidence at the start of the case and focusing on the merits of its fair use defense, OpenAI chose obstruction.”

OpenAI rejected the allegations. “As the Times’ case weakens and they’ve been forced to drop claims against us, they’re persisting with their efforts to invade the privacy of people who have nothing to do with this case, including by making these blatantly false allegations,” OpenAI spokesperson Drew Pusateri told Reuters. “We’ll continue defending our users’ privacy and the long-established principles of fair use.”

The publishers allege that OpenAI deleted billions of relevant ChatGPT conversations or made them unsearchable. They also argue that an OpenAI employee later testified that the company had performed multiple searches for news publishers’ content, contradicting earlier representations about the company’s technical limitations.

A sanctions memorandum posted by Ars Technica says the publishers want the court to bar OpenAI from relying on a disputed 20 million-log ChatGPT sample, find that ChatGPT’s output logs include or would have shown substantial use of the publishers’ copyrighted material, instruct the jury on those findings and award fees and costs tied to the discovery fight.

Those remedies would matter because discovery disputes can shape the trial record. If the court finds OpenAI failed to preserve or produce relevant evidence, the ruling could affect what arguments OpenAI can make later and what conclusions a jury may be allowed to draw from missing or incomplete records.

The Times sued OpenAI and Microsoft in 2023, alleging that millions of Times articles were used without permission to train AI systems that now compete with publishers as sources of information. OpenAI and other AI companies have argued that training models on large bodies of text is protected by fair use, a theory now being tested across lawsuits from authors, artists, music labels and news organizations.

For publishers, the issue goes beyond training data. They argue that AI chatbots and AI search summaries can answer readers’ questions using journalism without sending traffic, licensing revenue or subscribers back to the organizations that reported the information. Media Copilot has been tracking the same pressure point in coverage of Google’s AI accuracy problem and The Times’ warnings about AI companies using journalism without permission.

At the same time, publishers are taking different approaches to the AI economy. Some are suing. Others have signed licensing deals with AI companies. The Associated Press announced a deal with OpenAI in 2023, while other media companies have made agreements with OpenAI, Google, Meta and Amazon.

The sanctions motion could increase pressure on both sides. A ruling against OpenAI would give publishers leverage in court and in licensing talks. A ruling for OpenAI would strengthen the company’s argument that publishers are using discovery to intrude into user privacy and commercially sensitive systems.

Either way, the case shows that AI copyright fights are becoming data-governance fights. The central questions are no longer only what AI systems were trained on. They are whether companies can prove it, search it, preserve it and explain it in court.

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