Month: December 2025

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Nieman Lab Prediction 2026: Editors will start tackling the 5% challenge – and it won’t be fun (at first)

The advances of generative AI have put those in charge of newsrooms on an emotional rollercoaster. While 2023 and 2024 were the years of reckless experimentation (“Hey, look what these models can do!”), in 2025, AI realism took over. Great ideas turned out to be hard to implement, costly, or solutions looking for problems (“Nice, but it’s not serving anyone!”). Putting strategy back into AI development became key.

This is why 2026 is likely to become the dip of the ride. Because now, the strategy needs to be filled with life. And while editors at media conferences widely agree that AI will force newsrooms to focus on unique, original journalism and experiences that create value for their audiences and deepen customer connections, some detailed data analysis will make many of them feel queasy. Because the result will often be not that different from what an editor recently revealed at an industry gathering: Only 5% of a subset of his brand’s content was original journalism. The subtext was clear, of course: The rest could have been done by an AI. Welcome to the 5% challenge.

Expect many newsroom leaders to become busy next year figuring out what exactly makes their brand stand out in the emerging sea of content. And even harder: finding a way to scale the 5% (or maybe 20%) to proportions that guarantee their journalism’s survival. Because let’s face it, the era of the web has been the age of copy-and-paste journalism. And this is exactly what (once) younger journalists have been raised to do in the past 20 years or so. Sitting behind the screen all day and competing for reach was the job. The word “reporting” — picking up stories from the streets by looking at things and talking to people, face-to-face or on the phone — was converted into the phrase “reporting on the ground,” which sounded as if leaving the comfort of the office was an award-worthy niche discipline.

For leaders, doing all of this will involve conveying some hard truths to many newsroom inhabitants: telling them that their daily work has to change — and fast. Converting agency copy into a snappy story — the AI has already done it. Doing some service journalism because customers safely clicked on it — the chatbot will have been there already. Upselling subscriptions with branded recipes — maybe, as long as ChatGPT still spoils the dish with hallucinations. Unfortunately, “stop doing” is among the hardest disciplines for any kind of enterprise. Because other than running exciting experiments and excelling in the innovation department, stopping routines and common practices is neither sexy nor does it bring about career advantages. To the contrary, it means robbing people of things they love to do, or are at least proficient in. And it takes away the status and power that was attached to practicing them. Speaking of rollercoasters, there will be some uncomfortable circles at the bottom of this.

There are four areas where media brands can scale the human-made part of their journalism

But here comes the uplifting part: Focusing one’s journalism on “the real thing” (again) will be fun — for seasoned hacks and creator-type newcomers alike. And it can also help bridge the newsroom generation gap. While younger colleagues can learn from the more experienced ones research and source-building skills for access and investigations (including persistence and picking up a phone), older ones will profit from everything that the Insta-and-Spotify generation can bring to the desk, like video, podcasting, data research, and brand-building competencies.

There are four areas in particular where media brands can scale the human-made part of their journalism: First, with strong personal brands who will play out their authenticity and humanness to connect with audiences (plenty has been published about news creators in 2025). Second, with deep expertise in niche areas that AI-generated content cannot provide because it is prone to converge around the average. Third, with investigations that make news consumers proud of “their” news brand. And fourth, with strong local journalism that is deeply rooted in its communities — in most cases, AI won’t go there. Creators who understand their formats and their stuff can figure in all of these areas, of course.

The sizable rest can safely be left to the workings of AI, where agents will do a much faster, more targeted, and personalized job than humans could have done, provided humans do the necessary prep work for accuracy. Markus Franz, chief technology officer of Munich-based Ippen Group, predicts that with agentic AI, the current “human in the loop” principle will be replaced with a “human on the loop” approach in the future that helps with scalability.

In all of these scenarios, journalism jobs will move into two quite different directions. One set of roles will lean toward the more techie side. They will need to shape the new AI-mediated world of journalism, ensure scalability that adheres to the quality standards of journalism, and build compelling products for customers that make them connect directly with the brand. On the other side, we will see the new “old-style” journalists who do everything to solicit exclusive information and/or establish themselves as personal brands. Talent will most likely have to pick sides early on, and it is essential that journalism education reflects and fosters this. As soon as everyone has settled into their new seats, the rollercoaster can go on its next climb.

This prediction was published with Harvard University’s Nieman Lab on December 16, 2025.

 

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AI-Washing: Whoever Has No Moral Compass Now Will Never Build One

At first glance, many media companies have tackled the subject of AI in an almost exemplary manner. They got off to a flying start, experimented, formed interdisciplinary teams, appointed AI directors and – after all, they do have a responsibility – developed ethical guidelines. Of course, the industry was also able to express outrage at a few moral outliers – “Sports Illustrated!”, “the Michael Schumacher interview!”, “Burda’s cookery magazine!” – but in many places, lengthy lists of “dos and don’ts” were intended to prevent the worst. It’s just a pity that most of these sets of rules are likely to prove, before long, to be a form of AI-washing. For they give the illusion of control that has long since slipped from the media companies’ grasp. To paraphrase a line from Rainer Maria Rilke‘s famous poem „Autumn Day“: Whoever has no moral compass now will never build one.

The long version is this: rapid technological progress and the power of tech conglomerates, coupled with economic and, in some places, political pressure, have created realities that even exemplary management finds difficult to cope with. This is suggested by research for the EBU News Report “Leading Newsrooms in the Age of Generative AI“, published in 2025.

First and foremost, there is the issue of ‘shadow AI’. One media manager observes that the biggest changes are not currently being driven by media organisations, but are arising simply because journalists are using AI tools. Unlike 25 years ago, when editors and reporters still had to be painstakingly convinced of the value of digital tools and platforms, AI tools are so intuitive to use that people employ them even more frequently in their private lives than at work, as a recently published study found – at least with regard to the US. A report by the Thomson Reuters Foundation supports this view for journalists in the Global South: 80 per cent of those surveyed used AI at work, but not even 20 per cent of their newsrooms had a corresponding strategy or policy in place. Yet within organisations, both groups can become a problem: the tech-savvy staff who overstep boundaries whilst experimenting, and the less tech-savvy staff who make mistakes out of ignorance, such as disclosing sensitive data.

Added to this is the fact that many ethical guidelines are not practical for day-to-day use. The BBC is no doubt proud that it has condensed its current guidance on AI into just nine points – plus sub-points. But one cannot expect editors, who are under such time pressure during their shifts that some do not even dare to go to the loo, to have internalised all the regulations. The workload is likely to push journalists even more towards using AI. Just as text from dpa reports has occasionally had to be used in the past, an LLM will be consulted in future if it saves time.

The rule that is currently most widely followed is particularly difficult to adhere to: ‘Human in the loop’ – a human should have the final say on AI-generated content before it is published . Even in day-to-day operations, editors overlook errors. When AI tools multiply the speed of output, humans reach their cognitive limits. And if they were to work meticulously nonetheless, they would inevitably prevent the efficiency gains hoped for by management. The ‘human in the loop’ principle undermines the scalability that is expected from AI, writes Felix Simon in a commentary for the Reuters Institute.

When in doubt, editorial teams wriggle out of the requirement with disclaimers. They state that content translated or produced using AI is labelled as such – in other words: they accept no responsibility for errors. This can work well and is accepted by the audience in some cases, for example with subtitles for TV programmes. Here, the desire for comprehensibility takes precedence, for instance for the hearing-impaired. However, it can also produce rubbish, as with articles from the Washington Post that are translated by AI and published in the Ippen Group’s publications. Furthermore, even in high-quality journalism, there are scenarios where rigid rules are of no help. If, for example, cloned voices were banned across the board, it would limit narrative possibilities. Even public service broadcasters have used voice clones of historical figures to bring contemporary history to life.   

In all these cases, guidelines tucked away on the intranet are of no help. A more effective approach is a mix of technical solutions, training and debate: desired applications must be automated within the CMS. Through experiments and training sessions, users can acquire knowledge of AI and learn how to work with it. And those who regularly discuss values – even in highly contentious cases – are more likely to reflect on them and act accordingly. Monitoring staff at every stage of research and production has never worked in journalism. Each individual must calibrate their own moral compass and follow it.

However, this is of little use if the management doesn’t have one. The owner of the Los Angeles Times, for example, recently ordered the editorial team to tag comments using a tool called the Bias Meter. The AI automatically alerts readers to opposing viewpoints. Clearly, the output isn’t being proofread by humans. Otherwise, someone might well have noticed that the machine had cast the Ku Klux Klan in a somewhat too favourable light. But those are details. No AI tool will ever be able to replace a lack of trust. Yet using AI in this way can destroy hard-won trust – both amongst staff and with the public.

What could, however, render ethical guidelines in media organisations entirely obsolete is the dominance of tech giants. The more AI is embedded in all the tools that everyone uses in their daily lives, the less users will question the values underlying them. The fact that a smartphone camera always makes the sky a little bluer than the one you see in front of you – fair enough. The fact that search engines make answers increasingly easy to digest thanks to AI – that’s fine. The fact that word processing programmes are increasingly acting as editors before an editor has even seen the piece – why not? Only the major organisations will be able to afford to embed their own standards in their systems, and even those may well be infiltrated by AI. The rest will be working with Office and the like.

None of this has to be a bad thing. Autopilots have made air travel many times safer; autonomous driving will achieve the same on the roads. Perhaps AI-assisted journalism will also manage to raise the standard of overall output significantly. After the devastation of the ‘reach’ era, that’s not such a difficult task for some publications. AI tools may even eventually help to implement ethical guidelines. The crucial question is whose rules these will be.

This column was published by the German industry publication Medieninsider in German on 17 March 2025.#