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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A Manhattan federal judge on Friday refused to dismiss the core of Reddit’s lawsuit against Perplexity AI, allowing the platform to pursue claims that the AI search startup illegally bypassed technical protections to scrape Reddit content without paying for a license.

The ruling doesn’t determine whether Perplexity broke the law. But it does keep alive a legal theory that could prove as important as copyright in the battle over AI training data: that circumventing a platform’s access controls can itself create liability.

U.S. District Judge Paul Engelmayer ruled that Reddit can continue pursuing claims that Perplexity and three data scraping companies unlawfully bypassed protections designed to limit automated access to Reddit content, according to Reuters. He also found that Reddit has standing to sue over the alleged misuse of posts created by its users.

The defendants include Lithuania-based Oxylabs, Russia-based AWMProxy and Texas-based SerpApi. Reddit alleges the companies extracted its content from billions of search results without permission and that Perplexity worked with at least one of them to obtain the data. Perplexity, which does not license Reddit’s content, denies the allegations.

While Engelmayer dismissed several secondary claims, he allowed Reddit’s central allegations—including conspiracy and unlawful circumvention—to move forward.

Perplexity argues Reddit is attempting to control access to publicly available webpages it doesn’t own, using security measures it didn’t create and on behalf of users who never authorized the lawsuit. The company says it will continue defending what it calls the open internet.

Reddit argues the issue isn’t whether its content is publicly visible but whether companies deliberately bypassed technical barriers to collect it at scale without permission or compensation.

SerpApi attorney Jeff Homrig echoed that view, arguing the company accesses public search results rather than Reddit itself and that publicly available information doesn’t become proprietary simply because a platform later decides to charge for access.

That distinction could have broad consequences across the AI industry.

Reddit has transformed its user-generated content into a licensing business, striking deals with Google and OpenAI while describing itself in court filings as the most frequently cited source in AI-generated answers. If companies can obtain the same data by scraping around access controls, the value of those licensing agreements is diminished.

The lawsuit is one of a growing number testing how AI companies acquire training data. Authors, record labels, news publishers and other content owners have all sued AI developers over the use of copyrighted material. Reddit is also pursuing a separate lawsuit against Anthropic in California state court over similar scraping allegations.

For publishers, platforms and AI companies, Friday’s ruling is significant because it points beyond copyright. A favorable ruling on Reddit’s circumvention claims could give content owners another legal lever to protect their data—and strengthen their hand in negotiating AI licensing agreements.

The case is still in its early stages. But by allowing the core scraping and circumvention claims to proceed, the Southern District of New York has signaled that the next major battleground over AI training data may not be copyright alone. It may be whether AI companies can legally get around the digital gates content owners have built.

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Starting August 2, the European Union will require companies to disclose when images, audio and text have been artificially generated or manipulated to look authentic, as the Guardian reports. The rules are part of the EU’s AI Act, and they could have a particular impact on publishers and other organizations that are increasingly using AI to produce content.

Under the new requirements, people must be told when they are interacting with an AI chatbot or viewing manipulated media. Synthetic content must carry a visible label as well as a digital watermark identifying it as AI-generated.

The rules apply to new AI systems entering the European market beginning August 2. Existing systems will have an additional four months to comply. And for publishers, there is another important provision: Text about matters of public interest must be labeled as AI-generated when there has been no human editorial oversight.

Companies that fail to comply could face penalties of up to €15 million.

There are some exceptions. Personal content is exempt, as are works that are clearly artistic, satirical or fictional. Labeling AI-generated content created before the rules took effect is encouraged, but not required.

The European Union says the goal is to make it easier for people to distinguish authentic material from synthetic content. The rules follow the June 10 publication of a voluntary Code of Practice on Transparency of AI-Generated Content, which lays out how AI providers and deployers can comply with the AI Act’s labeling requirements.

Sergey Lagodinsky, a Green member of the European Parliament, told the Guardian that the rules are about more than protecting the public.

“It is a matter not only of customer protection, it’s also a matter of democracy protection,” he said. “Making transparent this information is something which we need to preserve our democracy and the authenticity of facts online.”

But some technology companies and industry groups say the rules have become too broad.

The Computer and Communications Industry Association argues that guidelines issued in July expanded the definition of a deepfake beyond what lawmakers intended when they passed the AI Act in 2024.

“The label was meant to flag deceptive content,” said Boniface de Champris, CCIA Europe’s AI policy lead. “That distinction has been removed, so now almost everything gets labeled — a landscape in an advert is the same as a manipulated political speech… That doesn’t protect anyone, it just burdens commercial activity across the board.”

De Champris says the biggest changes may not be obvious on social media, where platforms already label much AI-generated material. He expects the rules to have more consequences for advertising, film and publishing — industries that are using AI at scale but do not always tell audiences when they do.

That could put news organizations and other content producers in the EU in a new position. AI-generated images, synthetic voiceovers and machine-written text about matters of public interest may now require disclosure under the rules. What was once a question of editorial policy could become a matter of compliance.

Some major technology companies have already taken steps in that direction. TikTok says it requires creators to label realistic AI-generated media and has labeled more than 3 billion pieces of content. Google says its SynthID watermarking system has been used on more than 100 billion images. And more than 180 organizations, including Google and Meta, have signed a voluntary code of practice supporting the EU’s transparency requirements.

Henna Virkkunen, the European Commission’s executive vice president for tech policy, says the broader rules are meant to strike a balance. She described AI as a “transformative technology” capable of bringing “extraordinary benefits,” while warning that the most advanced systems could create risks “on an entirely new scale.”

For publishers and other content producers, the next phase will be figuring out exactly where those lines fall — and what AI disclosure looks like when it becomes a legal requirement rather than an editorial choice.

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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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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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Thirty-seven hosts for home shopping network QVC voted Thursday to unionize with SAG-AFTRA, turning concerns over generative AI and the use of their voices and likenesses into a new front in the media industry’s growing labor battles. Only nine voted against the move, giving SAG-AFTRA roughly 80% support in a National Labor Relations Board election covering full-time and part-time presenters at the company’s West Chester, Pennsylvania, headquarters, according to The Hollywood Reporter.

The vote covers hosts who appear across linear television, livestream and shortform programming. While the bargaining unit is small, the fight behind it reflects a broader industry battle over a question becoming harder to ignore: who controls a performer’s image when companies can create synthetic versions of it.

SAG-AFTRA President Sean Astin framed the vote around that concern. “QVC, HSN and Omni Channel employees deserve fair compensation, AI protections and a stronger voice in decisions that affect their work,” he said in a statement, adding that the union’s 160,000 members are proud of the hosts for organizing.

QVC said it has historically preferred a direct relationship with employees but will “respect the outcome of the election” and begin working with SAG-AFTRA toward a first contract.

The organizing effort was driven in large part by concerns over generative AI. The Hollywood Reporter reported earlier this summer that hosts feared their images, voices and likenesses could be used without consent or compensation. In a petition delivered to management, the hosts said they “should have meaningful input into [their] role in the network’s future, and that this is best accomplished through a formal collective-bargaining process.” They also sought clearer standards around pay, promotions and job protections.

Those demands mirror the fight SAG-AFTRA already waged with Hollywood studios in 2023, when AI consent and compensation protections became central issues in the film and television contract that ended a monthslong strike. QVC hosts do not have the same bargaining power as scripted actors, but the underlying concern is similar: companies gaining the ability to create digital versions of a person’s face or voice without their permission.

The timing adds another layer of complexity. Qurate Retail Group, QVC’s parent company, filed for Chapter 11 bankruptcy protection in April after cutting 900 jobs earlier this year. The company is also shifting its business model toward live shopping on social platforms and streaming services as traditional linear television declines. SAG-AFTRA will enter negotiations with a company restructuring both its finances and its distribution strategy.

For other newsrooms and media companies leaning on on-camera talent, hosts, anchors, livestream personalities, the QVC case is a preview. As publishers experiment with AI-generated avatars and voice clones to expand content across platforms, the people whose likenesses power those systems are seeking contract protections before the technology gets ahead of them. The Media Copilot has tracked similar consent and compensation disputes emerging wherever generative tools touch a recognizable face or voice.

What QVC’s first contract with SAG-AFTRA ultimately includes on AI rights, consent and compensation could become a reference point for other retail media and livestream operations facing similar questions.

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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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Reuters Editor-in-Chief Alessandra Galloni says the news agency is already using AI to draft headlines and opening paragraphs, translate copy and distill information from press releases — offering one of the clearest examples yet of how generative AI is reshaping newsroom workflows.

Speaking after delivering the Andrew Olle Media Lecture at Australia’s ABC on July 23, Galloni told the Australian media industry news website Mumbrella that Reuters has incorporated AI into routine production tasks while keeping reporting and editorial judgement in human hands. She argued that offloading grunt work to AI doesn’t strip young journalists of a way in. It just changes what the entry point looks like.

Three decades ago, Galloni said, junior reporters spent much of their time on administrative tasks that AI can now automate. Today’s newcomers, she argued, are instead building skills in data journalism, visual verification, camera work and drone operation.

“There are many things that you can do that didn’t exist 30 years ago, like going into the visual verification team or the fact-checking team of a news organization,” she said.

Her broader point was that the core of the profession remains unchanged. Rather than spending their first years on repetitive production work, Galloni said young reporters should focus on finding stories, interviewing people and developing reporting instincts.

“The best thing that young journalists can train on is going out and finding news and talking to people,” she said. In her view, AI is simply another tool modern reporters need to learn, alongside a growing set of digital reporting skills.

For newsrooms watching their entry-level pipeline shrink alongside AI adoption, Galloni’s comments are a rare instance of a wire service leader naming the tradeoff directly rather than dodging it. Reuters isn’t hiding that AI is contributing to the drafting and translation work once assigned to junior staff. The bet is that those time savings are redirected into reporting, verification and technical skills AI can’t replicate.

Whether that bet pays off depends less on the technology than on newsroom investment. Automating routine work only builds better journalists if editors reinvest that freed time into mentorship and field reporting, rather than treating it as a headcount reduction.

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The Associated Press will let its journalists use AI to draft headlines, summarize documents and handle transcription and translation, according to updated newsroom standards the wire service released this week. What it won’t do is hand over the parts of the job that carry legal and reputational weight.

The guidance draws a firm line: AI can assist with specific tasks, but reporting, sourcing, editorial judgment and verification remain the responsibility of human staff. Every AI-generated output must be reviewed and edited by an AP journalist before anything reaches readers.

The approved uses of AI are limited to a narrow set of practical tasks. AI can support early-stage research and document summarization, help with transcription and translation, suggest headlines, story summaries and shot lists, and clean up grammar, spelling and search optimization. AP kept one prohibition intact — generative AI cannot be used to create, alter or enhance news photography.

The updated standards underscore AP’s hard line on image authenticity as AI-generated visuals become more widespread. The news organization has long classified photo manipulation as a fireable offense, and the new guidance applies the same standard to AI-generated imagery.

The update also expands the guidance in several areas. It establishes newsroom standards for verifying and reporting on AI-generated and manipulated content, requiring journalists to clearly identify and contextualize such material when it appears in AP coverage. It also introduces disclosure requirements when generative AI materially contributes to published work. Beyond the newsroom, the policy adds guidance for AI coding assistants used in software development, reflecting the technology’s growing role across the organization.

The disclosure requirement may prove to be the policy’s biggest test. While AP requires disclosure when generative AI materially contributes to published content, it does not specify what qualifies as a “material” role, leaving room for editorial judgment.

AP’s approach offers a benchmark for other publishers developing AI policies. The standards permit AI to assist with newsroom workflows while reserving editorial judgment for journalists.

The updated standards are likely to be closely watched by other news organizations refining their own AI policies. The organization treats AI as workflow assistance under human review, not as a byline replacement, and it pairs that with disclosure and content-labeling rules. These guidelines also land as regulators and labor groups push for formal rules, including the New York AI transparency effort backed by major unions that would require newsrooms to disclose AI use.

As more publishers move from experimenting with AI to formalizing newsroom rules, AP’s updated standards offer one of the clearest examples yet of where a major news organization is drawing the line: AI can assist the reporting process, but accountability for what gets published remains with journalists.

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Substack readers can now run a check on any post longer than 100 words to see how much of it an AI model likely wrote. The company rolled out the feature on July 21 in partnership with the detection firm Pangram, with the scan available on web and iOS and Android support promised later.

The tool works only on content published starting on July 21. Alongside it, Substack is giving writers a dedicated space to state whether and how they used AI in a given piece. The idea, per the company, is to set reader expectations rather than police anyone.

No AI detector is reliable enough to call a piece machine-written with certainty. Pangram uses a deep learning classifier trained on around a million documents rather than the older perplexity-and-burstiness heuristics, and it reports strong internal accuracy numbers. But The Atlantic examined how well Pangram actually performs and found the picture more complicated than the marketing suggests. False positives are a known problem across the category, and lightly edited or paraphrased AI text is far harder to catch than raw model output.

Substack did acknowledge those limits in its announcement post. It also hinted at further features tied to AI content and reader preferences without saying what they are.

Its acknowlegdment matters because a wrong flag carries real cost. A human writer who gets tagged as an AI user has little recourse in the moment, and the accusation sticks. Non-native English writers have historically drawn more false positives from detection systems, which raises fairness questions for a platform with a global base of newsletter writers. Pairing the automated score with a voluntary disclosure field is Substack’s hedge against that, letting writers put their own account on the record next to the machine’s.

For newsrooms and independent publishers, the move is a preview of how disclosure norms may harden across platforms. If readers start expecting an AI provenance label on every post, editors will face pressure to document their own use of the technology and to decide where the line sits between an AI writing assistant and AI ghostwriting. Publishers who have built AI into their workflows, a shift The Media Copilot has tracked closely, will want a clear internal policy before a third-party score answers the question for them.

The real test isn’t whether the detector works. It’s whether readers trust a score that Substack itself acknowledges can be wrong. The company is betting users will treat AI detection as one signal among many, not a definitive verdict.

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