GB News told staff in July that it was proposing to cut as many as 90 jobs, roughly a third of its workforce, as it introduced automated production workflows.

A spokesperson said the broadcaster “has led the way in introducing groundbreaking workflows in UK media” and that new positions would be created under the proposed structure. GB News had also introduced AI-generated sports bulletins on its radio service in 2024. But the company did not say AI alone accounted for the proposed cuts, or that it could operate with exactly 90 fewer employees.

The proposal is one entry in Press Gazette’s rolling tracker of journalism job cuts in 2026, which documents layoffs, buyouts, proposed redundancies and newsroom closures across the U.S. and U.K. Press Gazette counted at least 3,434 cuts in 2025, 3,875 in 2024 and about 6,000 in 2023. It has not published a comparable cumulative figure for 2026, so the tracker does not yet show whether layoffs are accelerating this year.

Recent entries show how varied the pressures are. Pink News proposed cutting up to 11 staff members after Snapchat began retiring its Shows and Publisher Stories formats, an important source of revenue for the publisher. Queen City Nerve, the Charlotte alternative publication, shut down after a proposed sale fell through. Walmart-backed gaming site Restart laid off its five-person editorial team. Four music publications also saw their editorial staffs reportedly gutted.

Other cuts have come during changes in ownership or newsroom structure. BuzzFeed cut about 180 employees after Byron Allen acquired the company. At the Chattanooga Times Free Press, more than 50 employees were laid off around the time Firecrown Media’s purchase of the newspaper took effect July 31. The sale had been announced to staff the previous day.

The Associated Press cut 20 U.S.-based journalists in May. In July, Press Gazette reported that the AP was planning up to 30 additional cuts while also planning a production hub in India. Those later cuts and the hub were proposals at the time, not completed changes.

AI is more explicit in some cases outside the tracker. E.W. Scripps eliminated 432 positions this year while CEO Adam Symson described a broader push toward automation and an “AI-powered” broadcast company.

Marketing firm Clickout Media also laid off writers at gaming sites including The Escapist and Videogamer as it shifted toward a smaller staff overseeing AI-generated content. And the outplacement firm Challenger, Gray & Christmas said AI was cited in 15,341 U.S. job cuts announced in March, about a quarter of that month’s total, according to a Media Copilot report.

Those examples show that AI is becoming one factor in newsroom restructuring. But the broader list does not support treating technology as the single explanation for journalism’s job losses.

Distribution remains another pressure point. Pink News depends heavily on Snapchat revenue. In Manitoba, the Free Press Community Review closed after a change in flyer distribution. Newsweek, meanwhile, has faced a steep decline in traffic while expanding other revenue streams. The Reuters Institute has tracked the broader changes in how audiences reach news as platforms and referral patterns shift.

Press Gazette says it will keep updating its tracker through the year. For now, the picture is less a single AI-driven wave than a collection of pressures — automation among them — pushing news organizations to operate with fewer people.

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Fourteen UK news organisations told the National Council for the Training of Journalists that graduates need more than a basic familiarity with artificial intelligence, Journalism UK reports.

The skills employers highlighted include critical prompting, fact-checking, context awareness and ethical judgement — especially knowing how to identify bias, verify AI-generated material and spot hallucinations, according to Journalism.co.uk’s account of what recruiters are asking of new journalism graduates.

That matters because the NCTJ remains a major route into British newsrooms. Its Journalists at Work 2024 survey found that 81% of UK journalists hold a journalism qualification, and 83% of those qualified journalists went through NCTJ programmes.

The training body is now changing how AI is taught and assessed. It says AI literacy will be integrated across existing parts of the Diploma in Journalism rather than treated as a standalone subject. AI will also appear in exams and portfolio work, with students expected to disclose and reflect on how they used AI tools.

The research behind those changes is relatively small. The NCTJ describes it as qualitative research based on discussions with 14 journalists and editors from national, regional, specialist and broadcast news organisations. The published executive summary does not identify the organisations or break the findings down by specific newsroom role.

Still, the pattern was consistent in one respect: everyone consulted was using AI in some form. Some organisations were moving ahead more aggressively, while most described their approach as “cautious innovation.”

The NCTJ also found widespread shortages in AI literacy inside newsrooms. That echoes a separate survey of 448 newsroom leaders across 86 countries, which found that skills gaps and staff skepticism are among the biggest barriers to wider AI adoption. Six in 10 respondents said their newsrooms offered no formal AI training.

For journalism students, the message is less about mastering a particular chatbot than about judgment. The NCTJ says training should emphasize when AI is appropriate, how to verify its output, how to recognize hallucinations and when human editorial control is essential.

Not every student is eager to embrace the technology. A Northeastern University ethics seminar found journalism students pushing back on AI more strongly than their professor expected. But that classroom experiment was small and American; it is better read as an example of the debate journalism schools are navigating than as evidence about UK graduates broadly.

The changes also arrive during a difficult period for newsroom employment. More than 2,300 journalism jobs were lost in the U.S. and U.K. in the first half of 2026, according to a Press Gazette tally we previously covered. But the NCTJ’s own research cautions against drawing a simple line between AI and those cuts. None of the people it consulted said AI had directly reduced the number of journalists in their newsroom at that stage.

That distinction is central to the NCTJ’s approach. It is not asking students to replace reporting skills with AI skills. Reporting, verification, media law, ethics and editorial judgment remain the foundation.

The new expectation is that graduates understand how AI fits around those skills — and, just as importantly, when it should not.

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Gaurav Misra spent about $50,000 to build and run a television news operation for a day, without hiring a single journalist.

About $30,000 of that went to Claude Code credits as Misra, the CEO of AI video company Mirage, built the operation himself. The result was the Mirage News Network, a 24-hour experiment in using artificial intelligence to produce something resembling a traditional television news channel.

The broadcast drew about 50,000 viewers on X and the livestream post generated 824,000 impressions, according to Variety. Mirage paid several accounts to promote the stream, meaning some of that reach was purchased.

The Mirage News Network ran for 24 hours on Aug. 11. Four AI-generated anchors, styled after television broadcasters from the 1980s and given names including “Tom Callahan” and “Marcus Sterling,” delivered stories licensed from Reuters that were already several days old.

Mirage used its Avatar X model to create the anchors, while ChatGPT’s image generator and Google’s Gemini text-to-speech technology helped produce other parts of the broadcast. The humans who appeared on screen came from Reuters video reports and stock footage.

Even the guests were partly synthetic.

Mirage recruited more than a dozen people, many of them venture capital professionals, who allowed the company to use their likenesses and approved scripts for their AI doubles to deliver. Billy McFarland, the organizer of the failed Fyre Festival, was among them.

Mirage does not employ journalists. Misra, a former Snap and Microsoft engineer, told Variety that he instructed the system to follow “general journalistic standards,” rather than a specific set of guidelines such as AP style or the Society of Professional Journalists’ code of ethics.

The company did disclose its use of AI. An on-screen graphic identified the anchors, graphics, guests and advertisements as artificially generated.

But the experiment also showed some of the problems that can emerge when a news operation has little human oversight. At one point, the broadcast incorrectly identified a woman appearing in a Reuters report as President Donald Trump. Mirage later posted a correction on X rather than correcting the error during the broadcast.

Dan Axelrod, chair of the Society of Professional Journalists’ ethics committee, told Variety he considered Mirage’s experiment a news delivery project rather than a news network. He called it “a false and misguided devaluing and deskilling of journalism.”

His committee proposed revisions to SPJ’s code of ethics the same week, as the organization considers how longstanding journalistic principles should apply as newsrooms adopt new technology.

Even some people inside Mirage treated the project more like an experiment than the future of television news. Engineer Jason Silberman described it on X as what happens “when the CEO starts tokenmaxxing too hard and spends $50k in a day on a marketing stunt.”

There is also little evidence so far that large numbers of Americans want AI to become their primary source of news.

A Gallup survey released in May found that 7% of Americans said they relied on AI for news to at least a moderate degree. Nearly 4 in 10 said a news organization’s use of AI would make them trust its reporting less.

For publishers, Mirage may be more useful as an experiment in the economics of automated news than as a model for replacing cable television.

Smaller AI-native news operations are already testing versions of the idea. Runtime Wire operates with one human editor and says its system rejects 97.7% of the stories it considers, leaving at least some editorial judgment with a person.

Disclosure is another unresolved issue. Mirage prominently labeled its synthetic broadcast, but research into AI labeling has shown that disclosure alone does not guarantee audiences will notice or understand those labels.

At the same time, the financial pressure pushing publishers toward automation is real. Bauer Media, for example, stopped commissioning freelance fiction writers for Take a Break as it began using AI to help produce stories internally.

Misra told Variety that AI-generated newscasts are “probably inevitable in the future.”

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Robert Sanchez publishes one newsletter covering Arapahoe County, Colorado, on Mondays and Wednesdays. On Tuesdays and Thursdays, he turns to neighboring Douglas County.

Every local byline in both newsletters belongs to him.

Together, the two counties cover an area larger than Rhode Island. Other news organizations have multiple reporters covering individual cities within Sanchez’s beat.

His job exists, in part, because OpenAI is paying to create it.

Sanchez was hired as part of a three-year partnership between OpenAI and Axios. OpenAI is funding the startup costs for 13 Axios Local newsletters and providing Axios employees with credits for its enterprise AI tools. In return, Axios allows OpenAI to train its models on the company’s freely available journalism, according to reporting by Issie Lapowsky for Columbia Journalism Review.

Axios announced the first four markets covered by the deal in January 2025: Pittsburgh, Kansas City, Boulder and Huntsville, Alabama. It added nine more this year.

Axios CEO Jim VandeHei has framed the experiment as a question of whether technology can lower the cost of local reporting without eliminating the reporter.

“Could we use AI to basically automate everything you need in a local market other than the journalist and the journalism itself?” he told CJR.

VandeHei has also said “AI will save local news,” an argument we previously examined against the economics of Axios’s model.

So far, those economics remain unsettled.

Axios Local has more than 2 million subscribers but is not profitable, which a company spokesperson told CJR was expected. VandeHei said he would consider the expansion “a great success” if each market became profitable within five years.

Axios expects to operate in 43 cities by the end of 2026. VandeHei eventually wants to reach 1,000. Local reporting jobs posted by the company in early August offered salaries ranging from $65,000 to $125,000.

One important part of the arrangement remains unknown: how much OpenAI is paying.

Both companies declined to disclose the value of the agreement. They also would not say whether it limits Axios’s ability to take legal action against OpenAI. OpenAI spokesperson Kayla Wood told CJR that the terms are confidential.

Axios generally does not disclose the partnership in its local job listings or in stories about OpenAI unless those stories involve media deals. VandeHei said the contract does not spell out an editorial firewall because both companies considered Axios’s editorial independence a given.

One Axios employee, who spoke anonymously to CJR, said the lack of transparency has made some reporters uneasy.

Axios is not unionized. At Politico, employees challenged their company’s use of AI through their union and won an arbitration that led Politico to shut down two AI tools.

The Axios deal also raises a broader question about whether partnerships between individual publishers and AI companies can do much to address the decline of local journalism.

“If you strike a direct partnership with an AI company, that benefits you but no one else,” Matt Pearce, policy director at Rebuild Local News, told CJR. “There’s a systemic problem, and you’re not really doing anything to address the systemic problem. If anything, you’re kind of benefiting from it.”

The first markets also aren’t concentrated in places with the least access to journalism. Aside from Huntsville, which has no daily newspaper, none of the original cities qualify as news deserts under commonly used definitions.

VandeHei called expanding into communities without adequate local coverage “the Holy Grail.” But he said Axios first needs to prove the model can work in established markets.

For other publishers considering similar deals, Axios’s experiment shows both what an AI company may be willing to provide and what it may ask for in return.

Axios received startup funding and AI credits that are helping it put reporters into 13 markets. OpenAI received the right to train its models on Axios’s freely available journalism. But key terms of the agreement — including its value and whether it affects Axios’s ability to sue OpenAI — remain confidential.

That makes the arrangement different from OpenAI’s grants to the American Journalism Project. And whether the Axios model can eventually support itself without OpenAI’s money remains an open question.

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At last week’s Black Hat security conference in Las Vegas, OpenAI disclosed new details about a hacking incident involving its own rogue AI agents. Reporters raced to publish. WIRED was among the fastest, but an outlet called RuntimeWire beat it by more than three hours, according to WIRED.

RuntimeWire had no reporter at the conference. In fact, it has no reporters at all.

The site is an AI operation run by Austin entrepreneur Ryan Merket. After spotting an OpenAI executive posting about the talk on X, Merket fed a transcript of the livestream to his AI agents while the session was still underway. RuntimeWire published about six minutes later.

Most days, Merket is even less involved. His AI tools find stories, then draft, edit, fact-check, illustrate and promote them. If an agent determines that a story poses little legal risk, it can publish without his review. Some stories are also translated, turned into a daily podcast or read by synthetic voices.

Since May, RuntimeWire has published nearly 2,000 stories by scanning court databases, forums, company filings and social media for tech news. The trade-off, however, is quality. Its OpenAI story included a typo in the subhead and muddled key details. The operation also costs about $100 a day. Merket told WIRED he managed it by iMessage from Big Bend National Park, where the site published more than 80 articles in a week.

RuntimeWire is not alone. Dakota Carrasco, a BlackRock analyst, runs an agentic newsroom called The Dissent in his spare time. Its invented reporter personas cover subjects including San Francisco City Hall and Giants games. Carrasco remains anonymous behind the bots and acknowledges that the articles do not yet consistently link to their sources.

The risks are significant. Merket is relying on machines to decide what is true, what is newsworthy and what could create legal problems. Northwestern professor Nicholas Diakopoulos, who leads the university’s Computational Journalism Lab, describes the current moment as experimental and questions how much demand exists for bot-written news sites. He is also skeptical that mainstream journalists would surrender control over the wording and framing of their work.

But research from his lab points to one potential advantage. In a forthcoming paper, Diakopoulos and a colleague found that chatbots including ChatGPT and Claude surfaced AI-written sources 16 percent of the time across four topics. That could create an audience for AI newsrooms if assistants increasingly direct users to synthetic articles.

For publishers, the immediate challenge may be less about quality than cost and speed. An operation running for about $100 a day can compete with established tech outlets on live events and data-driven scoops — precisely the kinds of routine coverage that already strain newsroom budgets. As we have tracked at The Media Copilot, established publishers from Business Insider to The New York Times are bringing AI into their workflows. Merket is taking the idea further by using AI to break news, not simply repackage it.

Pete Pachal, founder and CEO of The Media Copilot, sees a limit. Building relationships with sources, he says, will remain a human job. But for covering product launches or combing through large datasets, he sees agentic newsrooms as a natural evolution of the technology.

Merket says RuntimeWire follows journalistic standards, including contacting subjects for comment and publishing corrections. So far, it has issued three. But he has also retracted accurate scoops about startups when their founders asked him to, calling it a favor from one founder to another.

That may be where the difference between running an AI news operation and running a newsroom becomes clearest. A reporter’s job is not only to get the story right and publish it quickly. Sometimes it is also to publish something a source would rather keep quiet.

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E.W. Scripps has eliminated 432 positions and 126 open roles since the start of the year, cutting 12% of its workforce as it restructures local news operations around automation.

CEO Adam Symson laid out the numbers on the company’s second-quarter earnings call this Thursday, saying Scripps intends to become an “AI-powered broadcast journalism company,” according to TheWrap.

The cuts have landed hardest at local stations. Of the total, 268 layoffs were disclosed earlier this week, most affecting employees at Scripps’ local television outlets.

“We’re leaning into AI, automation, technology and the centralization of some roles,” Symson said, describing the changes as a fundamental shift in how Scripps produces local news.

The financial case for the cuts is straightforward. Scripps expects the restructuring to generate $100 million in annualized savings. Its broader transformation plan is projected to increase EBITDA by $125 million to $150 million by 2028 through a combination of cost reductions and revenue growth. Symson also said the company is moving toward a 24-hour streaming news model.

Scripps’ second-quarter results were weak. Revenue fell 9% to $490.4 million, and the company reported a net loss of 34 cents per share. But investors welcomed its cost-cutting plans, sending shares up more than 20% in midday trading Friday.

Symson acknowledged the human cost. He called the process “painful” and “full of difficult decisions,” while arguing that the changes were necessary for the company’s financial health.

“We are not wavering on our commitment to quality journalism,” he said.

Local television has faced years of pressure from cord-cutting, shifting viewing habits and declining advertising revenue. Pew Research Center data has documented flat-to-declining revenue and audiences for local TV news over much of the past decade.

Automation and centralized production can help a station group cut costs. But they can also reduce the number of people reporting, producing and verifying the news that makes it to air.

Scripps described the overhaul as a “revolution” but has not disclosed which newsroom functions it plans to automate with AI. The company has yet to say whether the technology will be limited to tasks such as scheduling, captioning and playout or extend to editorial work such as writing scripts, selecting stories and producing broadcasts.

For other broadcasters, Scripps is becoming a test case for whether a station group can make deep cuts and still maintain the quality and breadth of its local journalism.

If Scripps delivers the promised savings without visible declines in accuracy or local coverage, other broadcasters facing similar financial pressure may follow. If coverage suffers, the company’s AI strategy could look less like a transformation of local journalism and more like a rationale for reducing costs.

Scripps, which also owns the ION broadcast network, expects the transformation to continue through 2028. The next several earnings calls will offer a clearer test of whether an “AI-powered” newsroom can deliver the financial gains the company has promised without weakening the journalism that remains.

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A translation of a mass shooter’s journal written in Faux Cyrillic. A scraper that pulled every public meeting minute from a Texas county website. Tens of thousands of leaked emails from a Chinese surveillance firm, made searchable with a large language model.

Each of those reporting efforts won or was a finalist for a Pulitzer Prize this year. And each relied, in some way, on AI.

Nieman Lab’s Andrew Deck reports that eight Pulitzer honorees disclosed AI use to the judging committee in 2026: five winners and three finalists. That’s the most since the Pulitzer Prizes began requiring AI disclosures in 2024—and it points to a shift in how journalists are using the technology.

In the two years before that, reporters mostly used older forms of machine learning — embedding models for data visualization, for example, or pattern-recognition tools to analyze satellite imagery. This year, commercial large language models did more of the heavy lifting, especially when reporters faced mountains of documents.

The approach was similar across this year’s Pulitzer winners. At The Wall Street Journal, computational journalist John West and his colleagues built a custom scraper to collect records from Kerr County, Texas, after deadly summer floods. They then used an internal tool called WSJPT to summarize every page and flag references to previous flooding events. Reporters still read each flagged section themselves.

“We aren’t obviating the need for human investigation of a pile of documents,” West said. “Instead, we’re trying to sort the pile so the most relevant stuff is right at the top.”

At The Minnesota Star Tribune, engineer Dana Chiueh used an enterprise ChatGPT account to analyze screenshots of a Minneapolis church shooter’s journal. The model identified the writing as Faux Cyrillic and produced a first-pass translation of more than 600,000 words.

The team then used Google’s NotebookLM to identify recurring themes and had two Russian-language academics at St. Olaf College verify key passages. Their review caught several errors, including one that mischaracterized the shooter’s motivation.

The reporting won the Pulitzer Prize for Breaking News.

The Associated Press used large language models to make tens of thousands of leaked documents searchable for its Pulitzer-winning investigation into American technology companies’ role in China’s surveillance state.

But reporters did not simply trust what the models surfaced. They manually reviewed documents flagged by AI, independently checked the accuracy of AI-generated summaries and did not quote from those summaries, said AP investigative journalist Garance Burke.

The New York Times flipped the usual workflow. For its investigation into the Securities and Exchange Commission’s retreat from crypto enforcement under the second Trump administration, reporters manually read and classified more than 10,000 documents. They then used OpenAI’s GPT-5 to conduct a second pass, flagging discrepancies for reporters to review.

In this case, AI was used to check the humans — not the other way around.

For newsrooms, perhaps the more revealing detail is what readers never saw.

The Wall Street Journal did not disclose its use of AI in the flood investigation at publication. West said the tools functioned essentially as a more sophisticated search system.

That gap between disclosing AI use to a prize committee and disclosing it to the public is at the center of an increasingly important debate over newsroom standards. It’s a tension that has surfaced repeatedly as news organizations figure out when AI use is significant enough to tell readers about.

Pulitzer administrator Marjorie Miller said the industry now has a clearer understanding of where AI can be used appropriately, such as data collection and analysis, and where its use raises more questions, including writing and editing.

Next year, after controversies over AI-generated text in prize-winning literary works, the Pulitzers will add an AI disclosure question to their book entry forms.

“AI is here to stay,” Miller said. The committee, she added, will continue asking entrants to demonstrate that a human produced the work.

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Reuters treats AI as a research assistant that must show its work. The BBC requires a human sign-off before any AI-assisted story runs. The Guardian will only let staff use it once a senior editor has approved the specific task. Three of journalism’s most prominent outlets, three distinct answers to the same question — and together they show there is no single blueprint for the AI-powered newsroom.

A new comparative study published by Nieman Lab examined how Reuters, the BBC and The Guardian have approached AI deployment, finding that each outlet has built its own framework around editorial priorities, governance and audience trust rather than embracing a uniform set of tools. The research analyzed public AI policies, editorial guidelines, trial reports and industry presentations released through 2025.

The study suggests AI adoption in journalism is increasingly less about whether to use the technology and more about how news organizations establish controls over its use.

Reuters has positioned AI as a reporting assistant that speeds journalism without replacing editorial judgment. Its in-house tools include Lynx Insight, which analyzes financial data in real time, and Fact Genie, which helps reporters process corporate press releases. Journalists must independently verify AI-generated claims before publication under its standards. Market reporting also provides unusually fast error-correction signals, since traders spot bad information quickly — a less forgiving model than political reporting or investigations, where a factual error can sit unnoticed far longer.

Reuters Editor-in-Chief Alessandra Galloni has described AI as a “force multiplier” that helps journalists analyze large document collections and identify patterns more efficiently, with governance checkpoints built in at each stage to preserve editorial accountability.

The BBC has taken one of the industry’s most cautious approaches, prioritizing transparency over rapid deployment. It permits AI for specific tasks such as At a Glance, which summarizes long articles, and BBC Style Assist, which reformats local stories in house style — a task the broadcaster says can otherwise take about 30 minutes. No AI-assisted material runs without an editor’s sign-off first.

That caution is evidence-led: in October 2025, the BBC and the European Broadcasting Union published research showing AI assistants misrepresented news content 45% of the time through faulty sourcing, fabricated details and outdated information. The broadcaster later introduced AI disclosure labels at the top of stories.

The Guardian revised its guidance in March 2026 to permit limited use of generative AI for tasks such as generating image alt text, analyzing parliamentary documents and transcribing audio, provided the tools meet editorial standards and a senior editor approves where required.

The policy reflects the outlet’s broader philosophy that AI should support, not replace, journalists. “Our generative AI framework is designed to support our journalists’ expertise, never replace it,” the outlet said in a statement. “Our journalists are always accountable for the journalism they create, and use of these tools requires absolute rigor and responsibility.”

The Guardian’s reader-funded trust ownership model has also shaped its strategy, allowing the publisher to prioritize editorial independence over commercial pressure even as the newsroom gradually expands its use of the technology.

The findings illustrate an industry shift away from viewing generative AI primarily as a content-generation tool. Leading publishers are increasingly deploying it behind the scenes — for research, document processing, transcription, translation and newsroom efficiency — while keeping journalists responsible for editorial decisions.

The divergent strategies also reflect broader debates across the news industry over governance, transparency and the economics of AI. As publishers negotiate licensing agreements with technology companies while pursuing litigation over unauthorized use of copyrighted reporting, many are simultaneously developing internal policies governing how AI can be used inside their own newsrooms.

Nieman Lab’s analysis concludes that newsroom AI adoption is evolving into an organizational question rather than simply a technological one. Success, the report argues, depends not only on selecting AI tools but on establishing editorial policies, accountability mechanisms and workflows that preserve journalistic standards as AI becomes part of everyday reporting.

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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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