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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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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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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Runtime Wire has published 1,627 articles since launching in May, after scanning 71,796 potential stories and publishing just 2.3% of them, according to a profile in Talking Biz News.

The site covers the AI economy, from funding rounds and model launches to developer tools, infrastructure, executive moves and court filings. Its stories have drawn 205,000 pageviews.

And the newsroom has exactly one person on staff.

“I’m the founder and the only human,” said Ryan Merket. “The newsroom itself is software, a pipeline of AI systems that scans sources, researches, writes, edits, fact-checks, and produces the video and audio around the clock.”

Merket describes his job as part editor-in-chief, part engineer. He sets editorial standards, reviews coverage each day and builds the systems that handle the volume. He previously served as CTO at Microsoft for Startups and worked at Reddit and Amazon Web Services.

The pipeline monitors about 50 sources, including vendor blogs, changelogs, research feeds, social media and tips. Off-topic material, such as sports or crypto price chatter, is filtered out before scoring.

The remaining stories are evaluated by an AI curator against a written editorial standard: Is the story new? Does it matter to people building with AI? Does it come from a live primary source? Has Runtime Wire already covered the underlying event?

Two additional layers check for duplicate coverage and re-reports.

What happens next shows where the automation actually sits. A research step fetches and reads primary sources, including attached images, which are transcribed so image-only claims can be checked. Merket says the research brief is anchored to the current date, helping prevent old news from being presented as breaking.

A writing model with live web search drafts the headline, summary and story. An editor model then reviews the piece for depth and accuracy and can send it back for more research. A separate fact-checking pass tests specific claims against the live web.

For stories Merket assigns himself, he serves as the editor and reviews them before publication. In the automated lane, no human reviews the copy before it goes live.

Runtime Wire has not generated revenue yet. Merket says its monetization infrastructure is already live, including sponsored placements in code editors such as VS Code and Claude Code, a jobs board and site sponsorships.

For now, he is running ads against house inventory to tune pacing, quality scoring and bot filtering before selling placements more broadly. The strategy is B2B-first, targeting developer-tools advertisers while keeping the site free for readers.

For newsrooms, the more revealing number may be the 2.3% publish rate. Runtime Wire is not betting on volume for its own sake. Its pitch is that most of what it scans never gets published.

That sets it apart from the AI content farms that have drawn scrutiny from watchdogs such as NewsGuard, which has tracked hundreds of unreliable AI-generated news sites. Whether a one-person newsroom can maintain that level of editorial filtering as it scales remains the bigger question.

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Anthropic put Claude Opus 5 on sale today at $5 per million input tokens and $25 per million output tokens, the exact prices it charged for the previous Opus 4.8. According to Anthropic’s announcement, the model reaches close to the intelligence of its higher-end Fable 5 model at half the cost, and it now serves as the default model on Claude Max and the strongest option on Claude Pro.

The company is leaning hard on benchmark numbers to make its case. On Frontier-Bench v0.1, Anthropic says Opus 5 beats every other model and more than doubles Opus 4.8’s score at a lower cost per task. On ARC-AGI, a test built around novel reasoning problems, the company reports Opus 5 scoring three times higher than the next-best model. On Zapier’s AutomationBench, which checks whether a model can run a business task end to end, Anthropic claims a pass rate roughly 1.5 times the nearest competitor at the same cost.

The recurring theme in the launch is verification. Anthropic describes Opus 5 checking its own work before handing it back. In one Frontier-Bench task, the model was asked to rebuild a machine part in 3D code but given no way to view the drawing, so it wrote its own computer vision pipeline to pull the geometry from raw pixels. In another example, it found the root cause of a bug in an open-source package manager that the community’s own patch had missed.

Early-access customers echoed that framing. JetBrains said the model catches its own logical faults during planning rather than after. A legal-tech tester reported first-turn redline scores nearly double Opus 4.8. Box measured an 8% overall improvement over Opus 4.8, with 17% gains on due-diligence workflows. These are vendor-supplied quotes, so treat the precise figures as marketing rather than independent measurement.

On safety, Anthropic says Opus 5 is its most aligned model so far, scoring 2.3 on its automated misaligned-behavior audit, the lowest of its recent releases. The company also notes the model stays behind its Mythos 5 model on biology research and offensive cybersecurity. Notably, Opus 5 can find software vulnerabilities about as well as Mythos 5 but lags badly at writing exploits for them, which Anthropic frames as a deliberate safeguard. Its cyber classifiers block binary vulnerability scanning, penetration testing and exploit generation, with flagged requests falling back to Opus 4.8.

For newsrooms and publishers, the pricing is the story. Holding costs flat while claiming stronger reasoning and cleaner outputs matters for teams running document analysis, research summaries and data work at volume. The customer notes about tighter, more concise responses and fewer tool calls point to lower token spend per task, which is where AI budgets actually get decided. Publishers weighing model choices should still run their own tests against real workflows rather than trusting benchmark charts, a point we’ve made repeatedly at The Media Copilot.

Anthropic paired the launch with two beta features: mid-conversation tool changes that don’t break the prompt cache, and automatic API fallbacks that route flagged requests to another model instead of blocking them. A Fast mode runs about 2.5 times the default speed at twice the base price. The bet is that a cheaper, more careful default beats a smarter but pricier one for daily use, and the next few months of real deployments will show whether that holds.

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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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beehiiv is expanding beyond email publishing with a suite of new products aimed at keeping independent publishers and news organizations from relying on multiple software vendors to run their business.

At its Summer Release Event on July 16, the newsletter platform introduced four products: Community, a built-in discussion platform; Copilot, an AI agent for audience and business operations; programmatic advertising; and a redesigned visual editor. Together, the launches mark beehiiv’s broadest attempt yet to compete as an all-in-one publishing platform rather than just a newsletter service.

The expansion reflects a shift in digital publishing, where newsletter platforms are increasingly competing to own more of the publisher workflow, from audience engagement and monetization to AI-powered operations.

“We believe the next chapter of the creator economy and content businesses is about consolidation,” co-founder and CEO Tyler Denk said during the event.

For publishers, the most significant announcement may be Copilot, beehiiv’s first native AI product. Rather than serving as a writing assistant, the company describes it as an AI operator capable of analyzing subscriber data, identifying audience segments, drafting marketing campaigns, launching workflows and surfacing revenue opportunities through a chat interface.

The launch builds on beehiiv’s adoption of Model Context Protocol, an open standard introduced by Anthropic that allows AI systems to securely connect with external data and software. As more publishing platforms adopt MCP, AI tools are shifting from generating content to executing operational tasks across newsroom business systems.

beehiiv also introduced Community, a feature designed to let publishers host subscriber discussions inside their own branded websites instead of relying on platforms such as Discord, Slack or Facebook Groups. Paid subscriber communities, moderation tools and podcast integration are built into the feature.

For news organizations, the move reflects a growing emphasis on first-party audience relationships as publishers seek to reduce dependence on social platforms and create additional value for subscribers.

The company also expanded its advertising business with programmatic newsletter ads that automatically match advertisers with newsletters based on audience characteristics and campaign performance. The system is intended to fill unsold inventory alongside direct advertising deals.

beehiiv said publishers on its platform now receive more than $1 million per month through its advertising network and have generated more than $50 million in subscription revenue.

The final launch was a redesigned visual editor that previews how newsletters and website content will appear before publication while supporting email, web pages, automations and recommendations from a single interface.

The announcements highlight how newsletter platforms are evolving into broader publishing infrastructure providers at a time when many news organizations are looking to simplify technology stacks and automate business operations. Rather than stitching together separate tools for newsletters, communities, advertising and audience management, publishers increasingly have the option to consolidate those functions within a single platform.

That consolidation could reduce software costs and technical overhead, particularly for smaller newsrooms and independent journalists. At the same time, it also concentrates more of a publisher’s audience data, monetization and workflow inside a single vendor, raising familiar questions about platform dependence as publishing infrastructure becomes more centralized.

beehiiv also previewed upcoming podcast advertising features, including dynamic ad insertion, signaling that the company intends to expand further into audio publishing as it broadens its reach beyond newsletters.

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It’s the first week of March, and the journalism industry has already absorbed a wave of layoffs that would have defined a full year just a few years ago.

Press Gazette’s rolling 2026 tracker documents cuts at the Washington Post, Atlanta Journal-Constitution, Politico, Nexstar Media Group, Vox Media, Bustle Digital Group, CNBC, the Wall Street Journal and more — all within the first two months of the year. In 2025, the full-year journalism job cut count reached at least 3,434 in the UK and US. In 2024, it was at least 3,875. This year’s pace suggests both figures will be eclipsed well before summer.

The specifics

The Washington Post has proposed cutting hundreds of staff — roughly one-third of the organization. The Atlanta Journal-Constitution announced approximately 50 cuts, or 15% of its workforce. Politico started the year by trimming 3% of staff.

At Nexstar Media Group, cuts have hit on-air talent and reporters across multiple major markets. The Los Angeles Times reported that “several on-air veterans” were cut at Los Angeles’s KTLA, at least three on-air positions were eliminated at New York’s WPIX and 21 people were cut at Chicago’s WGN — including nine reporters and anchors. WGN also eliminated six news writers and three technical director positions.

“A lot of really good people lost their jobs today, and it’s a shame,” WGN weekend morning anchor Sean Lewis said, per the Chicago Tribune.

At CNBC, a newsroom restructuring to merge its TV and digital operations will result in nearly a dozen layoffs including the website’s managing editor, though the network says it expects to hire more than 40 new editorial roles across platforms over the next year.

AI’s role: contributing factor or convenient cover?

The relationship between AI adoption and these layoffs is murky — and worth being careful about.

Newsrooms facing financial pressure are quick to cite digital disruption, changing consumption habits and advertising headwinds. AI is part of that story, but it’s not yet clear how large a part.

Mediabistro’s analysis of the media job market notes that the combined toll from one major merger alone — roughly 10,000 positions eliminated, about 8% of a merged workforce — reflects economic consolidation as much as automation. Cuts at companies like Amazon and Block have explicitly cited AI in their public messaging. Media companies have been more circumspect.

What’s happening in many newsrooms is a combination: cost pressure accelerated by the deterioration of search-driven referral traffic (Google’s AI Overviews have measurably reduced click-throughs to news sites), the slow collapse of print advertising revenue and a genuine rethinking of what roles are essential as AI tools absorb more routine tasks.

The result is fewer reporters, thinner copy desks, and more pressure on the journalists who remain to produce more.

What it means for the industry

Several things are simultaneously true right now:

The economic model is broken for many local and regional outlets. This is not new, but 2026 is producing a more acute phase of the collapse.

AI is being adopted most in precisely the places that have the least capacity to vet its outputs. Resource-strapped local newsrooms — the ones most likely to experiment with AI-drafted copy — are also the ones least likely to have robust fact-checking infrastructure.

Some cuts are being reframed as transitions. CNBC says it will net-add editorial roles. Iconic Media (formerly National World), in cutting 17 jobs at two city websites, says a net increase of 40 to 50 positions will follow as it pivots back toward embedded local journalists.

Whether those hires actually materialize — and in what form — is the real question. The pattern of media companies announcing new digital-first roles to soften the blow of cuts to traditional newsroom jobs has a long and frequently disappointing track record.

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If you’ve been even half-watching AI lately, you’ve probably run into Matt Shumer’s “Something Big Is Happening” essay,or, at minimum, the tidal wave of takes it kicked up. Shumer’s basic claim is simple: his own coding workflow has shifted from writing code to prompting, reviewing, and signing off on AI output that’s close enough to “done” to feel uncanny. It’s framed as a warning to knowledge workers everywhere: AI has effectively absorbed my job, and yours is next.

There’s already a small library’s worth of response essays picking apart what Shumer gets right and where he leaps too far, and I’m not trying to add another spine to the shelf. But journalism is knowledge work, too, and it recently had its own—slightly less viral—brush with the same existential questions.

The editor of Cleveland.com (a.k.a. The Cleveland Plain Dealer), Chris Quinn, wrote a column describing how a college student who had applied for a reporting job withdrew their application when they found out how the publication uses AI. Besides leveraging the tech to help generate story ideas, the newsroom developed an “AI rewrite specialist” to write stories based on the material that reporters gather. By ditching writing, according to Quinn, their reporters have been able to reclaim an extra workday each week.

The backlash was predictably vicious. On X, Axios reporter Sam Allard earned a lot of likes by comparing what Cleveland.com is doing to being an “AI content farmer,” while various veteran journalists on Substack expressed various degrees of outrage and dismay. Most of the reaction was along the lines of this piece from journalist Stacey Woelfel: “Writing is an integral part of the reporting process.”

The newsroom’s new fault line

That last line is true, but it’s also not the whole story. What Quinn describes can’t be waved away quite so cleanly, because newsrooms have been unbundling reporting work for decades. Reporters regularly collaborate on one article, with one person taking the lead on the draft while others supply interviews, documents, and context; nobody argues the supporting reporters somehow didn’t do “real” reporting. And in breaking-news moments, reporters often text, email, or phone in their notes to an editor or writer who turns the raw feed into publishable copy.

We all understand, at least implicitly, that reporting and writing aren’t the same skill—even if the best journalists make them feel inseparable. What Quinn and Cleveland.com seem to be doing is using AI to make that separation explicit, formal, and scalable.

This also fits the popular, almost comforting story people tell about “responsible” AI in the workplace: let machines take the repeatable work they can do faster, so humans can spend their limited hours on the parts that actually require judgment and presence. For reporters, that’s the human stuff: calling sources, learning what’s new, asking the second question, and earning trust over time.

And here’s the uncomfortable part: AI is now legitimately good at writing. A lot of what we’ve seen over the past few years hasn’t helped its literary reputation (yes, we’re all tired of the rampant em-dashes and the “it’s not X—it’s Y” bits). But if you use the strongest models—and you’re even mildly intentional about prompting and editing—they can deliver clean, coherent, competent prose.

If we’re being honest, “competent prose” is exactly what a large chunk of daily news requires. Many, if not most, reported stories are built to transmit basic information about what happened, with minimal interpretation, and they’re often written in AP style—a set of constraints that’s effectively a template. It’s not quite code, but it’s functional writing, optimized for speed, clarity, and accuracy. The job is to get the facts right, add context, and move.

Seen that way, the reporter isn’t removed from the process so much as repositioned inside it. Shumer describes becoming a supervisor to an AI building machine; journalists may find themselves supervising writing bots, making sure a story is shaped correctly out of the material they’ve gathered. In Quinn’s newsroom, reporters have final say over the copy.

What gets lost when nobody writes

None of this guarantees a happy ending. Some writers can’t report, some reporters can’t write, and plenty of people are good at both. So what happens when the job is redesigned to force a choice? Do you become a feature or opinion writer, where voice and craft are the value, or do you specialize in the reporting side and let an “AI rewrite specialist” (or whatever comes next) handle the draft?

This leads to the biggest worry: skill-building. Even if Quinn is right and this system truly buys back time, how do junior journalists become better writers if they aren’t writing every day? When Woelfel says writing is integral to reporting, I think he means it’s integral to storytelling—the act of deciding what matters, what comes first, what gets emphasized, and what gets left out, all in service of an audience. That’s curation and prioritization as much as expression.

This is the point Ben Affleck was getting at when he drew his famous line between AI as a craftsman and AI as an artist. Craft can be taught, outsourced, templated; artistry is harder to mechanize. But it’s also hard to become an artist if you never get reps as a craftsperson.

The irony of Shumer’s essay is that even as it argues AI will soon disrupt most knowledge work—and even name-checks journalism as an industry in the crosshairs—it’s written in a distinctly human voice. I honestly don’t know if he used AI to fully or partially write the piece, but I’m certain that if he did, he also was meticulous about every word.

That’s the sliver of optimism here. Even if we push some of the craft of writing onto machines, we may not lose as much as the most alarmed reactions assume. Audiences still want a human touch; if that touch moves upstream—from drafting sentences to shaping the narrative and deciding what’s true and important—it’s still a touch. It’s true that no one wants to read AI slop. But it might turn out that the most valuable reporting skill in the future will be the ability to turn slop into stories.

A version of this column appeared in Fast Company.

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