A Google search for “Burnham social care” on July 30 surfaced something new at the top of the page: BBC, Guardian and Caring Times articles stacked in a Top Stories carousel directly inside an AI Overview, according to Press Gazette.

The placement is part of a broader shift in how Google handles breaking news in AI-generated search results—and it creates a new dilemma for publishers weighing whether to opt out of Google’s AI features.

Google began rolling out the embedded Top Stories carousel in June. When it appears, it replaces the standalone Top Stories box that traditionally sits below an AI Overview, putting publisher links closer to the top of the page instead of forcing users to scroll through AI-generated text to find them.

The format is already showing up at meaningful scale.

Data from news SEO firm Newzdash shows that 15.5% of trending-news searches in the US that triggered Top Stories displayed the module within an AI Overview rather than in its traditional position.

The analysis covered more than 17 million Top Stories appearances across 40-plus countries during the 30 days ending July 28. So far, Newzdash has observed the embedded format only in the US and UK.

Entertainment was the category most likely to trigger the placement, accounting for 35.1% of cases in the US and 31.5% in the UK World news and sports followed, with sports appearing more often in the UK than in the US.

Newzdash founder John Shehata described the change as a “double-edged sword.” Google has said it wants to make links more prominent in its AI search experiences, and embedding the full Top Stories carousel does exactly that.

“We do not yet have comparative clickthrough data, but it should create a stronger opportunity for clicks than pushing Top Stories further down the page,” Shehata said.

But the new placement comes with a catch: Publishers may have to accept AI-generated summaries of their content to qualify for it.

Breaking news was once relatively insulated from Google’s AI answers. That protection is fading. Nearly half of Google search results pages now carry an AI Overview, according to Semrush’s tracker, putting news publishers increasingly inside the AI-generated search experience.

Google recently added Search Console controls allowing publishers to exclude their content from AI Overviews and AI Mode. The UK rollout followed a ruling by the Competition and Markets Authority.

Newzdash found that Top Stories appeared either inside an AI Overview or as a standalone module — never both. That means publishers that opt out of Google’s generative AI features could lose access to the embedded placement, with no guarantee that Google will show the standalone Top Stories module elsewhere on the page.

Shehata said publishers should distinguish between two different Google controls.

Blocking Google-Extended in robots.txt restricts the use of content for model training and grounding and should not affect a publisher’s eligibility for Top Stories. The Search Console exclusion is different: It determines whether a publisher’s links can appear in Google’s AI features at all.

The trade-off lands amid a growing debate over whether publishers should block their content from AI search. Opting out can keep a publisher’s content from being summarized by Google, but it may also remove the publisher from one of the most prominent referral opportunities Google has introduced in years.

And in an AI search environment where being cited by name increasingly matters, the embedded Top Stories carousel is more than a technical change. It is a new strategic choice for news publishers: accept a place inside Google’s AI experience, or risk disappearing from one of its most visible news placements.

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UK publisher digital revenue fell 4.55% in the first quarter of 2026, ending four straight quarters of growth, according to the Digital Publishers’ Revenue Index run by the Association of Online Publishers and Deloitte.

The survey, reported by Press Gazette, covered 13 publishers, nine business-to-consumer and four business-to-business. Richard Reeves, managing director at the AOP, called the drop the “first tremors in an earthquake being felt across the industry” as AI-generated answers and shifting audience habits keep readers from clicking through to source sites.

The decline was uneven. Some 62% of respondents still reported revenue growth, the highest share in a year, which the AOP said points to the heaviest losses being concentrated among a minority of publishers most exposed to changes in the information ecosystem.

The numbers that fell fell hard. Recruitment classified revenue dropped 44.84%, other classified was down 38.17% and off-platform revenue fell 20.27%. The AOP attributed much of that to people getting what they need from AI answers without visiting a publisher. Digital audio revenue sank 46.98% year on year for the second quarter running.

The click-through data backs up the concern. Separate AOP research found only 26% of ChatGPT users say they would click at least one media link in a response, rising to 34% for a Google Search carrying an AI Overview. Users are 18% less likely to click through to a source when an AI Overview sits at the top.

The “miscellaneous” category, covering revenue that doesn’t fit the main buckets, posted the single biggest decline. The AOP suggested AI substitution of publisher content across referral channels was a factor. It also flagged agencies Dentsu and WPP pulling out of The Trade Desk’s OpenPath initiative over concerns about ad placement and hidden fees.

Not everything went down. Digital display advertising rose 5.06%, likely on the back of more direct-sold premium deals. Every respondent now ranks advertising a high business priority, up from 75% a year earlier. Online video grew 1.29%, sponsorship 0.91% and subscriptions a thin 0.63%.

Reeves said the display turnaround “must be commended and demonstrates the quality of the advertising product that premium publishers provide.” Andy Cowen, lead partner for telecoms, media and entertainment at Deloitte, said the display growth shows the value premium content still holds but warned the drops elsewhere point to an “urgent need for publishers to adapt.”

For newsrooms, the report reads as a warning about cost. Every publisher in the index now says it will prioritise cost reductions, up from 50% a year ago, and every one says acquisitions are a priority, up from 25%. That mirrors wider pressure across the sector, where journalism’s workforce is shrinking as AI and new consumer habits reshape the industry.

There is one thread publishers can pull on. AOP research found a reader’s trust in an AI answer depends on their perception of the news brand cited in it, which underlines how much AI companies still rely on verified publisher content even as they starve those publishers of clicks. Whether that dependency translates into deals or dollars is the next thing the revenue index will measure.

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ChatGPT has begun refusing requests to write in the style of named authors, marking a notable change in how OpenAI’s chatbot handles imitation prompts. As reported by Ars Technica, the system now steers users toward describing literary traits rather than directly invoking a writer’s style.

The Media Copilot was able to replicate the result on July 28. After asking ChatGPT to write a short story in the voice of Ernest Hemingway, the chatbot replied, “I can’t write in the exact style of a specific author or closely imitate a copyrighted work’s voice. I can, however, write an original passage that draws on some broad characteristics often associated with Ernest Hemingway—plain language, understated emotion, concrete observation, and spare dialogue—without closely imitating his distinctive expression.”

The change is less about the output than the prompt. Requests that explicitly name an author may now be refused, but prompts describing the same stylistic traits—such as minimalist prose, clipped dialogue or a gothic mood—can still generate comparable writing without invoking a specific writer.

The apparent shift comes as OpenAI continues to face multiple copyright lawsuits over its AI models and outputs. While those cases primarily concern training data rather than stylistic imitation, they have intensified scrutiny over how AI systems reproduce or emulate copyrighted creative works, prompting companies to adopt more cautious safeguards around requests that closely mimic identifiable authors.

Other chatbot makers have drawn the line differently. Ars Technica cites a No Latency study that found Google’s Gemini complied consistently with author-imitation requests, while Perplexity refused and redirected them. Anthropic’s Claude and Microsoft Copilot fell between those positions, complying while adding qualifications. The uneven treatment means a refusal in one product does not prevent a writer or editor from trying the same prompt elsewhere.

For newsrooms and publishers, ChatGPT’s new author-style restrictions underscore the need for AI policies that govern editorial practices rather than any single technology provider. Internal guidelines should define whether staff may request imitation of living authors, deceased writers, competing publications or an organization’s own house style, while requiring disclosure and human review before AI-generated text is incorporated into published work.

OpenAI has not, based on the material cited here, announced a formal written-text policy that matches the chatbot’s current behavior. Until it does, publishers should expect the boundary to be defined largely by the product itself: prompts that explicitly name authors may be declined, while requests describing the same stylistic qualities in broader terms can still generate a response.

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Newsmax’s current and archived reporting will feed Meta’s AI-powered search and discovery tools under a licensing agreement announced Tuesday, giving the social media company another publisher partner as it builds news answers into its products.

The agreement reported by The Desk covers Meta services including Facebook, Instagram and WhatsApp, and extends to current and future consumer devices sold by the company. Meta will use the material to train its AI-supported search and discovery tools, while those tools will also link users to Newsmax stories and videos and generate short summaries from written work.

Christopher Ruddy, Newsmax’s chief executive, welcomed the deal in a statement to The Desk: “Newsmax applauds the significant resources Meta is putting into AI to keep America at the forefront of this emerging technology.” He added that the publisher wanted to help users reach timely, high-quality journalism through AI technologies.

The reported terms do not include a price or other financial details. That leaves a central question unanswered for publishers weighing similar deals: what compensation reflects the value of an archive, a daily reporting operation and traffic that may be intercepted by an AI-written answer before a reader reaches the original article.

Newsmax joins a growing group of right-of-center outlets that have signed Meta agreements, including Fox News Media, the Daily Caller and the Washington Examiner. The Desk also reports that Meta has reached content arrangements with News Corp, Warner Bros. Discovery, USA Today Company and People Inc.

Meta’s stated aim is broader than adding another political perspective. In comments cited by The Desk from December, the company said it wants Meta AI to become more responsive, accurate and balanced, particularly during breaking news events when its AI systems struggle to keep pace. Meta is integrating the assistant across its consumer products, placing search, recommendations and conversational answers inside the same ecosystem.

That goal remains untested. Licensing news publishers gives Meta a clearer legal basis to use their reporting than scraping the web or relying on unresolved fair-use claims. But it does not answer how Meta AI will choose sources, attribute reporting, summarize competing accounts or weigh conflicting information. Adding more publishers expands the pool of reporting. It does not, on its own, ensure balanced results.

For newsrooms and publishers, the Meta-Newsmax agreement underscores how AI licensing has become as much a distribution strategy as a rights negotiation. As more publishers strike AI licensing agreements, attention is likely to shift from financial terms to attribution, referral traffic, transparency and the distinction between training rights and real-time content use.

Meta’s next test is execution. The company will need to show that licensed journalism makes Meta AI faster, more reliable and better sourced without reducing publisher reporting to an invisible input. Newsmax has secured a place in that effort. The success of the agreement will ultimately be measured less by how much Newsmax content appears in Meta AI than by whether AI-generated answers still create an economic incentive to produce the original reporting.

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MIT Technology Review’s paywalled articles will now be available through Muck Rack‘s monitoring platform under a licensing deal that expands communications teams’ access to artificial intelligence and emerging technology coverage. In its announcement of the deal, Muck Rack said it is the first communications platform to license the publication’s content.

The agreement gives Muck Rack customers access to the publication’s full editorial output, rather than only material visible on the open web. That helps eliminate a blind spot created by paywalls, giving companies a fuller view of coverage, competitors and reputational risks.

Muck Rack has been building a roster of direct publisher deals, recently adding Bloomberg Media and STAT, according to the announcement. MIT Technology Review, founded at MIT in 1899, covers the business, policy and social effects of technology as well as technical developments.

Natan Edelsburg, Muck Rack’s chief partnerships officer, said the arrangement reflects the company’s effort to work directly with publishers while giving users access to trusted AI reporting. Ted Hu, senior manager of licensing at MIT Technology Review, said the deal takes the publication’s reporting to communications professionals beyond its usual journalist and technologist audience.

Muck Rack is pitching the deal as a way to help communications teams track how brands appear in both AI-generated answers and traditional news coverage. The company said earned media, referring to unpaid editorial coverage such as news articles, accounts for 84% of citations in responses from ChatGPT, Claude and Gemini, while journalism makes up 27% of sources cited by those AI systems. Muck Rack did not disclose its methodology, time frame or underlying dataset, so the figures could not be independently verified.

The licensing model is more concrete than those numbers. It gives Muck Rack permission to distribute and search reporting that would otherwise be restricted, while giving a publisher a commercial route into enterprise monitoring. It also differs from the unresolved question of whether AI companies need permission to train on publishers’ archives.

For publishers, the deal reflects a broader effort to monetize journalism beyond subscriptions and advertising. As news organizations challenge search engines and AI companies over the use of their reporting, licensing agreements provide a way to generate revenue while ensuring their content is available through enterprise platforms. The arrangement also highlights the growing value of credible journalism as AI systems and communications professionals increasingly rely on it.

Muck Rack’s next challenge is proving customers will pay for licensed access when many media monitoring tools still rely on publicly available content. If more publishers sign similar agreements, media monitoring could become a new licensing channel for news organizations rather than another way their content is used without compensation.

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Trust in AI answers rises and falls with the credibility of their sources. More than 90% of people trusted an AI response when they completely trusted its cited source, but that figure plunged to about 10% when they completely distrusted the source, according to new findings reported by Press Gazette.

The figures come from an Ipsos survey of 1,000 UK adults for the Association of Online Publishers’ Artificial Intelligence Publisher Impact Study. The findings show that AI can distill reporting into a polished answer, but users ultimately judge that answer by the credibility of the news organization it cites.

The effect extended even to publishers respondents felt neutral about. Trust in the AI answer was only about 25% when the cited source was rated neither trusted nor distrusted. The survey measures correlation, not causation, and reflects stated attitudes rather than observed behavior. Even so, the pattern is unmistakable.

Trust also affected reported willingness to visit the underlying publisher. Nearly half of people who somewhat or completely trusted a cited source said they would click at least one link in an AI response. That finding fits a wider pattern covered in The Media Copilot’s reporting on news brands and AI clicks: the publisher’s name may still be what persuades users to leave the chatbot, even as AI interfaces give them fewer reasons to click elsewhere.

There is an uncomfortable counterpoint. Even when users completely trusted the cited source, nearly a third said they would stop at the AI answer rather than click through. That figure was similar among those who completely distrusted the source. A citation alone can make an AI answer more credible without delivering the visit, subscription opportunity, or advertising impression that paid for the original reporting.

The study also found that 37% of respondents did not know AI tools can fabricate information or sources. That rose to about 45% among 45- to 54-year-olds. The result matters because a polished answer can borrow authority from reputable citations while still getting a claim wrong, omitting context or inventing a detail.

AI companies have good reason to seek current, attributable reporting. OpenAI’s partnership with News Corp is one public example of the licensing deals that give chatbots access to professional journalism. Yet the confidentiality of many licensing deals makes it difficult for publishers to know whether they are being fairly compensated for the credibility their reporting brings to AI answers.

For newsrooms, the immediate task is less about winning back every lost referral than preserving the conditions that make their reporting worth citing. Clear attribution, strong archive pages, distinctive analysis and direct audience relationships matter when an AI answer becomes the first read. Publishers also need to decide which crawlers and products earn access.

The survey’s implication is clear. AI platforms are borrowing trust that publishers spent decades building, while publishers risk capturing only a fraction of the value it creates. As AI answers become the default gateway to information, the rules governing licensing, attribution and publisher control will determine whether publishers can still turn trust into revenue.

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Media OutReach Newswire says it will guarantee that client press releases appear in USA Today’s public-facing release section, part of a broader push by PR firms to optimize content for AI-powered search, according to the company’s own announcement.

The Hong Kong-based wire, which describes itself as the first global newswire founded in Asia Pacific, is framing the deal as an AI visibility play rather than a traditional PR win. Alongside USA Today, it has struck deals covering Yahoo Finance, the Associated Press and more than 770 other US news sites, as well as regional titles including The Arizona Republic, Detroit Free Press, Indianapolis Star, Milwaukee Journal Sentinel, The Tennessean and The Oklahoman.

The company says the strategy relies in part on JSON-LD schema markup, a structured-data format that labels key information in online content so search engines and AI systems can more easily interpret details such as a release’s author, date and subject. Media OutReach said it began adding the markup to its postings in March 2026, arguing that combining machine-readable data with broad distribution can increase the chances that client content appears in AI-generated answers.

“By improving the quality of our guaranteed news postings on trusted, Google-indexed news sites with domain authority, coupled with the direct delivery of press releases to journalists’ inboxes, Media OutReach Newswire has successfully helped many Asian corporations to build their brand reputation in the US market,” said Jennifer Kok, the company’s founder and CEO, in the announcement. She said the company’s journalist database covers more than 500 trade categories and 68,000 media titles.

The company also highlights the domain authority scores of partner sites, a third-party metric from Moz that is not a confirmed ranking factor for Google or AI systems. Media OutReach’s claims about improving AI visibility have not been independently verified, and there is no public evidence showing that JSON-LD tagging or guaranteed release placement directly affects citations in tools such as ChatGPT or Google’s AI Overviews.

For newsrooms and publishers, the takeaway is blunt: the AI-visibility market is now shaping how PR firms buy placement, too. When a wire service can guarantee a slot in a paper’s press-release section, that section stops functioning as editorial real estate and starts operating as paid inventory built for machine readers, a shift The Media Copilot has been tracking as GEO tactics move out of marketing departments and into wire distribution itself.

That raises a harder question for local papers. As guaranteed press-release sections spread across high-domain-authority sites, publishers will have to be clear with readers and with AI crawlers alike about where sponsored or wire content ends and staff journalism begins.

Whether JSON-LD tagging and wire placement actually affect AI citations is still unproven outside vendor claims. The real test comes when independent researchers, not the newswires selling the service, start measuring the results.

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The Delhi High Court handed OpenAI a major legal victory Friday, ruling that the company’s use of news agency ANI’s articles to train ChatGPT does not infringe copyright because it qualifies as fair reporting for research purposes under India’s Copyright Act, Reuters reported.

It is the first substantive court finding in India on whether AI companies can train large language models on copyrighted news content without a license. That question is still open in courtrooms in the United States and Canada, where OpenAI faces similar suits.

ANI first sued OpenAI in November 2024, alleging the company trained ChatGPT on its copyrighted news reports without permission and that the chatbot falsely attributed fabricated stories to the agency. Presiding over the ANI v. OpenAI lawsuit, Delhi High Court Justice Amit Bansal rejected the copyright claim, finding that ANI failed to prove ChatGPT had memorized or reproduced its articles in response to users.

The judge also rejected ANI’s claim over OpenAI’s storage of its articles, ruling that retaining the content for AI training is protected as research under India’s Copyright Act of 1957 and does not infringe the agency’s copyright.

The ruling contrasts with ongoing litigation in the United States, where The New York Times, the Center for Investigative Reporting and a growing number of publishers argue that OpenAI’s use of copyrighted material for AI training violates U.S. copyright law. Unlike India’s fair-dealing framework, which lists specific permitted uses, U.S. courts evaluate fair use case by case. In Canada, a coalition of Canadian news organizations, including CBC and The Globe and Mail, is testing a separate copyright framework in its own lawsuit against OpenAI.

The decision could reshape negotiations between AI developers and publishers in India, where the threat of copyright litigation may carry less weight after the ruling, It could reduce pressure on OpenAI and other AI companies to pursue licensing agreements with Indian news organizations, even as similar disputes continue elsewhere.

The ruling is not the final word in the case. It addresses ANI’s claims at this stage of the proceedings, and appeals remain possible. The judge’s finding on reproduction was also based on the evidence presented by ANI, not a broader conclusion that AI systems can reproduce copyrighted material.

Even so, India has become the first major jurisdiction to find that training AI models on copyrighted news content can qualify as protected research. As courts in the United States and Canada continue to weigh similar claims under different copyright laws, the divergence in legal approaches is becoming increasingly difficult for AI companies and publishers to ignore.

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Nine Entertainment, Australia’s largest locally owned media company, will cut around 30 newsroom jobs at the Sydney Morning Herald and the Age, blaming what its publishing chief called an “extreme state of disruption” caused by AI.

Tory Maguire, Nine’s managing director of publishing, delivered the news to staff on Tuesday, according to reporting from The Guardian. The reductions will come through a mix of voluntary and targeted redundancies. Maguire framed the move as an evolution rather than a straight cost cut, though financial pressure is evident.

“In the last 12 months, as we have discussed many, many times at the publishing town halls, we are in an extreme state of disruption because of AI,” she told staff.

Maguire put AI ahead of every prior shock the industry has absorbed. The internet and social media, she said, did not disrupt the business as much as AI is now.

The numbers behind that claim are becoming clearer. The Reuters Institute’s Digital News Report 2026 found 10% of news consumers worldwide now use AI chatbots to get their news, rising to 16% among people under 35. Meanwhile, fewer readers are clicking through from search engines, because Google increasingly answers queries with its own AI summaries instead of sending traffic to publishers.

Australian outlets face a compounding problem. Research from the University of Sydney found local journalism was largely invisible in AI-generated news summaries produced by Microsoft Copilot, which overwhelmingly surfaced US and European sources instead.

Nine’s own financials reflect the squeeze. Digital subscription revenue fell 6% last year, and Maguire said reader revenue stalled for the first time in three years, with the division under enormous pressure partly due to the popularity of AI search results. The company says it plans to retrain existing staff and hire for what it describes as digital-first, reader-savvy, data-informed roles.

The Australian Financial Review is exempt from this pressure. Maguire credited its head start, pointing to a paywall it has run since 2007, as evidence the AFR is further along in adapting than the two legacy mastheads.

This is not an isolated incident. Two years ago Nine cut 200 jobs, including 90 from the mastheads and the AFR, and in 2024 chief executive Matt Stanton warned of $100m in cuts over two years. That earlier round, tied to Meta abandoning the news media bargaining code, triggered industrial action and a wave of senior departures. The merger with Fairfax Media in 2018 shed another 144 roles.

For newsrooms elsewhere, the pattern here is worth watching closely. Publishers are now naming AI not as a future risk but as the immediate cause of headcount decisions, and the referral economy that funded much of digital journalism is thinning fast.

Whether retraining and new digital roles can offset the loss of search and social traffic is the open question. Nine is betting they can. The next set of subscription numbers will show whether that bet is paying off.

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As AI companies continue scraping the web for training data, some publishers are experimenting with a new tactic that doesn’t only block unwanted bots, but tries to waste their time and money.

Known as LLM honeypotting, Digiday describes the approach as a form of deception to lure AI crawlers into consuming plausible-looking but ultimately worthless content, aimed at making large-scale data collecting so computationally expensive that it becomes less economically viable. 

Who’s doing this? A small number of publishers and e-commerce companies are looking for alternatives to traditional bot-blocking. And while the technique remains early and experimental, it’s one way for media companies to protect their content amid a fight to create standards for how AI companies track, value and compensate journalism. 

A cybersecurity tactic adapted for AI

Cyberhoneypotting is a long-standing cybersecurity strategy. The technique is to build a decoy target for attackers—or LLM bots, in this case—that can lure bad actors away and even gather intelligence on their capabilities and methods. In this case, the goal is to make scraping content without compensation more costly than it’s worth. 

Simon Wistow, co-founder of content delivery network provider Fastly, describes the philosophy as one of “Chang[ing] the economics of attacking.” If abusing a system becomes significantly more expensive than the value gained, the entire model will become unsustainable, he argues. 

Applied to AI crawlers, the strategy is equipped against all automated visitors, regardless of whether they are operated by major AI companies or smaller third-party scraping firms. 

Publishers can implement the tactic in several ways. They can introduce subtle delays, difficult (for computers) problems to solve before admittance, or endless mazes of contents and files filled with meaningless AI-generated text. Some honeypotting techniques go even further and try to inject bad data into the bots’ training datasets, “poisoning” the AI results.

The tactic’s adoption

Large e-commerce brands are already testing the technology successfully, said Wistow. News publishers are also showing increased interest, although he declined to identify specific customers. 

Even so, skepticism towards the strategy remains. 

Frederick Jahn, co-founder of AI company Centennal, argues sophisticated scrapers can often detect or avoid honeypots altogether. 

“I think it’s a good concept, but more on a marketing level, and like a gimmick,” Jahn said. He argues that publishers would be better served by creating real barriers to stealth crawlers, who are often not shown maze pages. 

Supporters of honeypotting maintain that, even if most scrapers adapt, increasing operational costs across thousands or millions of requests could make smaller scraping businesses financially unsustainable. 

“If they could burn through that 10 million funding in one crawl then suddenly those businesses aren’t viable and suddenly the whole market collapses, and that’s kind of what you’re going for,” said Wistow.

Costs and limitations for publishers

The strategy isn’t free. Generating and serving millions of fake pages is more expensive than simply blocking unwanted traffic. And larger publishers with more resources are better able to plan and implement the strategy.

Wistow said the approach is unlikely to become widespread, in part because of the consequences of filling the internet with yet more intentionally deceptive content. 

“Hallucinations happen even with good data, just because of the way LLMs work,” said Wistow. “This is about changing the economics for the people abusing your site, not running some giant disinformation campaign.”

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