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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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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Tap the headphones icon at the top of a New York Times or New Yorker story and you may hear it read by an automated voice. The feature has spread across major news organizations, as publishers use AI-generated narration to give readers another way to consume their journalism.

In a Columbia Journalism Review analysis, contributing writer Jem Bartholomew examines how The New York Times, The Washington Post, The Wall Street Journal, The New Yorker, The Atlantic and Vanity Fair have adopted automated text-to-speech tools. ElevenLabs, the AI voice company that partnered with The New Yorker in 2023, said this year that it had surpassed $500 million in annual recurring revenue. The company offers more than 10,000 artificial voices and has held early talks with investors about a secondary offering that would value it at $22 billion.

The technology is already drawing significant use. About 20% of New Yorker subscribers listen to narrated stories, deputy editorial director Monica Racic told CJR. At The Wall Street Journal, the “Read to Me” feature, developed through a partnership with Microsoft that began in 2020, was used about 5 million times over the past year and had a 65% completion rate.

New Yorker editor David Remnick told Semafor that an ElevenLabs voice sounded “pretty damn good” and was “nearly instantaneous” to produce. ElevenLabs CEO Mati Staniszewski told Al Jazeera in February that the company’s technology could produce speech based on the contextual understanding of written text.

But CJR’s Bartholomew found limits in the technology. AI narrators can rush through passages that call for pauses, emphasize unexpected words and use simulated breaths or rising intonation at unnatural moments. The result can sound convincingly human while still feeling artificial.

Bartholomew found the difference most striking when he compared an AI narration of a 1997 New Yorker profile of Donald Trump by Mark Singer with Singer’s own reading of the piece for the audiobook version of his 2016 book, Trump and Me. Singer died in June.

The synthetic voice maintained a steady pace through passages that depended on irony, sadness and changes in tone. Singer’s original reading conveyed those shifts; the AI version largely did not. For Bartholomew, the comparison showed what can be lost when a piece of writing shaped by a human writer is delivered by a synthetic voice.

Despite the loss of tone and nuance, accessibility is one of the clearest arguments for AI narration. A Times spokesperson told CJR that the newspaper has experimented with automated voices for years as a way to make its journalism more accessible, including for people who are blind or have low vision. ElevenLabs says its impact program provides free licenses to nonprofits and people with accessibility needs.

Publishers also see narration as an additional way to reach audiences rather than a replacement for written journalism. Taneth Evans, the Journal’s head of digital, told CJR that the feature is “additive” and gives readers another way to engage with the newspaper’s work.

The New Yorker has drawn a line around fiction. The magazine does not use AI to narrate its fiction, which is read by authors whenever possible because the reading is treated as a performance.

AI narration gives publishers another way to put journalism in front of audiences wherever they are. But as synthetic voices become more common, newsrooms face a more consequential question: How much of a story’s meaning survives when the human voice is taken out of the telling?

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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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If you want to chart the shortest path to where AI in journalism gets uncomfortable, look at what happens the moment the machine is asked to write the story rather than just research it. It inevitably comes up, since the most obvious use case for generative AI is writing. It’s right there in the name—large language models (LLMs) are all about reading, organizing, analyzing, and conjuring words. That single fact is the reason so many working reporters have spent the past few years quietly recalibrating what their job even is.

The friction is no longer theoretical. As artificial intelligence systems get better at writing, a growing number of newsrooms are using AI to help not just with analysis, process, and ideas, but the actual words, too. That has surfaced real fights on the shop floor. Reporters at The Sacramento Bee recently objected to having their bylines put on content written primarily by AI.

I’ve been making this point in my AI trainings for a while now: putting AI-generated words in front of a public audience is one of the highest-risk applications of the technology. I should know, since AI-generated articles are a component of The Media Copilot’s editorial strategy. A playbook starts with an honest self-interview about what you’re doing: What is the medium? What exactly is the AI’s role? What’s the worst that could happen? There are more questions after those, and the answers turn into the rulebook everyone in the newsroom has to live by.

Arguably the most important section of that rulebook is disclosure, the mechanics of telling a reader when the words came from a machine. The most direct way to do so is with an AI byline. These usually get sterile, corporate-sounding names, such as the AI News Desk or Generative AI Services, along with their own author pages. That unambiguously lets the reader know that AI didn’t help just with research or ideas, but also with the words on the page. How much of the writing was actually machine-generated, which is usually the part readers care about, tends to live in a disclaimer at the bottom of the page.

Transparency has a price tag

On paper, the AI byline looks like a clean fix. It checks the transparency box, it’s an easy-to-read label, and it slots neatly into an existing system. Audiences even ask for it. A Trusting News study found that 94% of readers want disclosures on content that’s AI-written. All of which suggests the AI byline should be trending up as AI use in newsrooms climbs.

The trend line is going the other way. A 2025 audit of 186,000 articles in 1,500 newspapers in the U.S. estimated that about 9% of the content was partly or fully AI-generated, yet only about 5% of those articles included a disclosure. Prominent AI-byline experiments at Fortune and Business Insider were discontinued. That is not evidence of a broader retreat from AI writing. Nick Lichtenberg, business editor at Fortune, famously used AI to produce more than 600 stories in six months. At The Cleveland Plain Dealer, writing tools convert raw reporting into stories with final sign-off from the reporter, and the AI byline shows up only when the human contribution is minimal.

From my own perch covering this beat, the shift is visible: fewer robot bylines every quarter. Which isn’t to say they’re gone: CoinDesk marks AI assistance with the byline “AI Boost” and ESPN’s writing bots still get top billing, but they read as holdouts, not the direction of travel.

Three forces are pushing the AI byline out.

1. The visibility problem. Google says it doesn’t downgrade content simply because AI was used to produce it. Its guidance still leans hard on clear authorship, first-hand expertise, and accountability, though, and the company has said publicly that assigning AI an author byline is probably not the best way to disclose the use. A robot byline may not be a direct negative ranking signal, but it also strips out the human-authority cues that search and answer engines are built to reward.
   
   The data backs the intuition. In Graphite’s 2025 analysis, human-written articles made up 86% of the pages ranking in Google Search and tended to rank higher than AI-generated material. That doesn’t prove that AI authorship or attribution caused the difference, but the disadvantage is real and pointed in a consistent direction. That pattern shows up in our own experience at The Media Copilot. Our human-bylined articles show up in Google Discover and rank higher in Google Search than those published under our AI byline, The Copilot.
2. The trust paradox. The Trusting News study found that, although the vast majority of audiences want AI disclosures, their presence made 42% of respondents less likely to trust an article. Reuters Institute research surfaced the same shape at a wider aperture: 12% of readers are comfortable with fully AI news, versus 62% comfortable with fully human-written news. The label the reader asks for is the same label that erodes their trust when they see it.
3. Institutional memory. When generative AI was new, there were several high-profile failures of AI content. An AI byline welds a publisher to that history. By putting forward an AI byline, an outlet paints a target on every article that runs under it, ready for the screenshot industrial complex to fire at the moment something breaks.

Add it up and the AI byline has collected a lot of baggage in a short time, and plenty of publishers have decided it’s not worth carrying. However, that doesn’t translate into a pullback on AI generally, or even a pullback on AI-assisted content. The workaround most publications are quietly settling on is simple: keep the byline for the human and disclose the machine’s contribution in a note somewhere else on the page.

What the byline really is

The whole debate comes back to what a byline actually signals. The idea that the person named at the top of the article wrote each and every word has always been a fallacy. Editors, wire copy, fact checkers, headline writers, and spellcheckers all contribute actual words and sometimes whole passages to articles. Automated editing software takes this even further; anything substantially edited through Grammarly or a similar tool already carries wording shaped by AI.

The byline is not “I wrote all these words”; it’s “I stand by all these words.” And that unearths the biggest problem with AI bylines—they obfuscate responsibility. Without ownership, without someone prominently standing by what’s actually written, there’s little incentive to make sure it’s great writing. Every article that carries a robot byline gets marked as second-class writing, no matter how much of the work the AI actually did.

The Sacramento Bee episode cuts the other way, too. Writers will defend their names, hard, and they should. The path forward isn’t to force writers’ names onto AI content without their consent, but to give them the freedom to use the tools and take on the accountability that comes with signing their names to the output. The disclosure should scale with the machine’s contribution: Routine editing may need no note at all. Substantial drafting warrants disclosure. Largely automated reporting should spell out both the system and the human review that stands over it. Ultimately, though, the only label that really matters is whether a named human stands behind the result.

With the right policies and training in place, a publication can hand its writers wide latitude on AI while keeping accountability attached to a human. If the content is worthwhile, then over time those who use AI to amplify and accelerate their judgment will be successful. The ones using AI as a substitute for thinking will inevitably fail.

Human accountability is the scarce signal

So the AI byline isn’t dying, but it is being repriced. As machine text gets cheap, a human name that carries real accountability becomes the scarce and valuable signal. As the tools get better, they’ll continue to blur who wrote what. The constant, however, is simple: A human has to stand behind it. No one gets to outsource accountability to a machine.

A version of this column appears in Fast Company.

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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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More than half of newsroom leaders surveyed for a new global study said staff skepticism is the single biggest thing holding back AI integration, as reported in Press Gazette.

The Future Newsrooms Study 2026, from FT Strategies and WAN-IFRA, collected responses from 448 people across 86 countries, most of them editors-in-chief or executive leaders. It found 52% named “cultural resistance or skepticism” as the biggest barrier to wider AI adoption, and 61% blamed a lack of internal technical skills or expertise.

Another 45% pointed to missing strategic direction. Putting the numbers together reveals a pattern: newsrooms aren’t sure what they’re using AI for, staff don’t trust it and nobody’s teaching them how to use it well.

Six in ten newsrooms offer no formal AI training at all. Where training does exist, the report calls it “generic” and “not specific to journalistic needs.”

The study’s central recommendation is structural. Newsrooms that embed an AI authority inside the editorial team, rather than setting strategy from outside, see higher adoption and more confidence among staff. Yet 57% of respondents had no AI expert in the newsroom at all. As the report puts it, having someone “directly within the newsroom to advocate for AI in the editorial context matters to adoption rates.”

Confidence overall is thin. Just 14% of leaders were very or extremely confident their current tech stack was fit for purpose. One in five had no confidence in it whatsoever.

Lisa MacLeod, director of FT Strategies, framed the findings as a warning. Any newsroom “operating on the old playbook of optimising purely for reach and reactive, breaking news, is actively managing its own decline,” she said.

The report also flags a risk in how newsrooms measure success. A majority (43%) expect AI to cut newsroom headcount over the next three years, while newsrooms default to time savings as the main proof AI is working. That, the authors warn, orients newsrooms toward “doing the same work, just faster and with fewer people” instead of enabling journalism that wasn’t possible before.

For publishers, the takeaway is that the AI problem is a management problem. Buying tools solves nothing if editorial staff aren’t brought into the decisions, trained on journalism-specific tasks, and given someone credible inside the room to answer their questions. The tension between how newsrooms talk about AI and how they actually use it shows how fragile trust remains when tools arrive faster than the culture can absorb them.

AI use in newsrooms remains relatively limited. Most organizations use it for transcription and translation (78%), while only 10% have adopted autonomous AI agents, the highest level of agentic AI use, in any newsroom function. Text remains the main focus, with 97% of those surveyed using AI for written content.

Four years after ChatGPT launched, most newsrooms are still using AI as an assistant, not an agent.

“The data in this report—which will be the first of an annual research effort—provides a stark wake-up call,” MacLeod said. “The truth is that our newsrooms are not well prepared for a disrupted future.”

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

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

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

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

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

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

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

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