The backlash in McClatchy newsrooms and what it reveals about AI in journalism
The backlash that McClatchy is facing across its newsrooms says a lot about the tense moment journalism is living through right now. The company, one of the largest local journalism networks in the United States, decided to bet on an artificial intelligence tool to scale content production — and the reaction came fast.
On one side, the company sees technology as an ally to grow and reach bigger audiences. On the other, the journalists in the newsrooms see a real threat to their jobs, their autonomy, and the value of what they produce every single day.
This is not a simple fight, and there is no clear villain in this story. What we have is a debate that is far from over — and one that goes well beyond McClatchy’s hallways. 👇
What is McClatchy’s content scaling agent
To understand the full scope of this controversy, you need to know exactly what tool sits at the center of it all. During a team meeting that lasted about an hour last month, Eric Nelson, McClatchy’s vice president of local news, introduced what he called a powerful addition to our toolkit.
Nelson was promoting the company’s new content scaling agent — a tool that works as a summarization engine powered by Claude, the language model developed by Anthropic. According to the executive, the tool can help reporters find new audiences, new angles, and new entry points for their stories.
The pitch, at least as leadership framed it, was straightforward: use AI to generate more versions of existing stories, reaching different audiences with different approaches. In practice, that would mean taking a published piece and creating automated variations of it — summaries, shorter versions, pieces with a different focus — all without a journalist necessarily having to rewrite each version by hand.
And that is exactly where things get complicated. The phrase that best sums up the philosophy behind the initiative shows up right in the headline of the exclusive investigation published by TheWrap: more stories, more inventory. In other words, the logic is essentially about scale — produce more content to generate more ad space and, consequently, more revenue. An equation that makes sense in financial reports but sounded like an alarm inside the newsrooms.
The immediate reaction: unions step in
The reaction from McClatchy journalists did not come out of nowhere. It is part of a broader movement that has been building in newsrooms around the world, where media professionals are increasingly aware — and worried — about the rise of AI tools in the workplace.
What made the McClatchy case particularly explosive was the concrete action from the unions. The unions at the Miami Herald, the Sacramento Bee, and the Kansas City Star — three of the most important outlets in the group — filed formal grievances against the company. These are not small publications. They are newspapers with deep traditions, loyal reader communities, and editorial teams that feel they were left out of a decision that fundamentally changes the nature of the work they do.
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For the unions, the company was making unilateral decisions about a change that directly affects working conditions, jobs, and the professional identity of journalists. That alone would be enough to spark conflict. The central issue raised in the grievances is that the content scaling agent was rolled out without prior negotiation with workers — something that, in unionized workplaces in the United States, is considered a serious violation of collective bargaining agreements.
The exclusive report from TheWrap brought new details about how the tool actually works in practice, which fueled even more frustration. With more concrete information in hand, journalists were able to better articulate their criticisms and strengthen the arguments behind the union grievances.
McClatchy and the financial context behind the decision
McClatchy owns more than 30 news outlets spread across the United States, including regional newspapers with decades of history. The business model for local journalism has never been easy, but in recent years it has gotten even tighter, with declining advertisers, shrinking print subscriptions, and digital competition that keeps growing.
It is worth remembering that McClatchy went through a bankruptcy process in 2020 and was acquired by an investment fund, Chatham Asset Management. Since then, the pressure for operational efficiency has increased significantly. In that context, adopting automation technology is not just a strategic choice — for many inside the company, it feels like an almost inevitable consequence of the new financial reality.
It was within this high-pressure environment that the company started exploring the use of AI tools to automate parts of content production. The idea, at least on paper, was to free up journalists to focus on more complex and investigative reporting while AI handled the more mechanical and repetitive tasks. But inevitable does not mean painless, and that is exactly where the backlash gained momentum.
The problem is that the execution of this idea generated far more friction than the company probably expected. According to reports that surfaced through TheWrap’s investigation, the AI tool adopted by McClatchy was not being used just as an assistant for simple tasks — it was being integrated more broadly into the editorial workflow, which set off a massive alarm inside the newsrooms.
Why journalists reacted so strongly
Journalists started questioning how far this technology was being used to complement human work versus gradually replacing it. And that doubt alone was enough to create an atmosphere of distrust and tension that quickly turned into public backlash.
AI-generated content raises serious ethical questions for journalism:
- Who is responsible for inaccurate information published by an automated system?
- How does the reader know they are consuming content generated or modified by a machine?
- Is there enough transparency in this process?
- Are editorial standards being maintained when scale is the priority?
These questions do not have simple answers, and the journalists who raised them were doing exactly the work expected of them: questioning, investigating, and demanding accountability. The backlash, in that sense, was not just an emotional reaction to the fear of losing jobs — it was also a legitimate professional response to a change that was implemented without proper editorial care and without engaging the teams affected.
Beyond that, there is a very practical component at the heart of this discussion. Quality local journalism depends on context, on relationships with the community, on sources built over years, and on a deep understanding of the reality of each city or region. An AI tool, no matter how advanced, does not have that kind of institutional knowledge.
It can organize data, structure text, and identify patterns, but it cannot replace the human perspective that understands why crime went up in that specific neighborhood, or what is really behind the crisis in a small city’s local government. When journalists say AI threatens the quality of content, that is exactly what they are talking about — a dimension of the work that still cannot be replicated by any machine. 🤖
The role of Claude and Anthropic in this story
An important technical detail that TheWrap’s reporting revealed is that McClatchy’s content scaling agent is powered by Claude, the language model from Anthropic. For anyone following the generative AI space, this is not a minor detail.
Anthropic positions itself as a company focused on AI safety, with an approach that prioritizes the responsible development of language models. Claude is considered one of the most sophisticated models on the market, competing directly with OpenAI’s GPT and Google’s Gemini. McClatchy’s choice of this specific technology suggests the company was looking for a model with strong summarization and text generation capabilities — something Claude genuinely excels at.
However, no matter how good the model is, the way it gets implemented makes all the difference. A language model is a tool, and like any tool, its impact depends on who uses it and how they use it. In McClatchy’s case, the implementation appears to have prioritized scale over transparency and dialogue with editorial teams, turning a potentially useful technology into a flashpoint for conflict.
A debate that goes well beyond one company
The McClatchy case is emblematic, but it is far from isolated. Over the past two years, several major American publications — like Sports Illustrated, CNET, and G/O Media — have also faced serious controversies related to the use of AI for content production. In some cases, automatically generated articles were published with serious factual errors. In others, the lack of transparency about the use of the technology created credibility crises that cost the brands involved dearly.
The pattern that emerges from these stories is always similar: media companies, under financial pressure, bet on automation as a quick fix, and the result is a backlash that mixes worker outrage with public distrust.
What makes this debate so complex is that neither side is completely wrong. Journalism companies truly face an unprecedented economic crisis, and ignoring the available technology would be, at the very least, naive. AI has a real capacity to help newsrooms do more with fewer resources, as long as it is used responsibly and transparently.
On the other hand, journalists are right when they demand to be included in decisions about how this technology gets implemented. Changes this significant in the workplace need to be negotiated, not imposed — and journalistic content, which plays an essential role in democracy, deserves special care that goes beyond productivity metrics.
Lessons for the future of AI in journalism
The McClatchy episode offers some clear lessons for any media organization considering adopting artificial intelligence tools in its newsrooms.
The first is about communication. Presenting an AI tool in an hour-long meeting, no matter how detailed the presentation, does not replace a genuine process of consultation and negotiation with the affected teams. Journalists need to be part of building these solutions from the start, not informed after the decisions have already been made.
The second lesson is about transparency with the public. If content is being generated or significantly modified by AI, the reader needs to know. This is not just an ethical issue — it is a matter of survival. Public trust is the most valuable asset any journalism outlet has. Risking that trust in the name of scale is a dangerous bet.
The third lesson is about purpose. The logic of more stories, more inventory might work for an e-commerce business, but when applied to journalism, it needs to come with a real commitment to quality. Producing more content only has value if that content is relevant, accurate, and useful to the community it serves.
A barometer for what lies ahead
At its core, the backlash McClatchy is experiencing is a symptom of something bigger: the lack of a clear, consensus-driven model for how to integrate AI tools into journalism without compromising the fundamental values of the profession. Transparency for the reader, editorial accountability, respect for the work of journalists, and content quality all need to be at the center of any strategy that involves automation.
The formal grievances from the unions at the Miami Herald, the Sacramento Bee, and the Kansas City Star are more than isolated labor disputes. They represent a milestone in the relationship between newsrooms and AI technology — and will likely serve as a reference point for other media outlets navigating this same territory.
What happens in the coming months inside McClatchy could set standards for the entire industry. If the company manages to find a balance between technological innovation and respect for editorial work, it could become a positive case study. If it continues down the path of implementation without dialogue, the backlash is likely to grow — and the costs, both in reputation and in lost talent, could end up being much higher than the savings AI promised to deliver.
Without that balance, any attempt at modernization will keep running into the same resistance — and perhaps generating the same kind of crisis McClatchy is trying to overcome right now. 📰
