How news organizations should overhaul their operations as the gen AI threatens their livelihoods

AI is potentially disruptive to many organizations’ business models. In few sectors, however, is the threat as seemingly existential as the news business. News ought to matter to all of us since a functioning free press performs an essential role in democracy—informing the public and helping to hold power to account. And, there are some similarities between how news executives are—and critically, are not—addressing the challenges and opportunities AI presents that business leaders in other sectors can learn from, too.

The following reflection by the author is based on his participation at Aspen Institute conference entitled “AI & News: Charting the Course,” that was hosted at Reuters’ headquarters in London. The conference was attended by top executives from a number of U.K. and European news organizations.

Most of the reflections still evolve and remain so around modest impact of AI—mostly around making existing workflows more efficient.  There was active debate among the newsroom leaders and techies present about whether news organizations should take a bottom-up approach—putting generative AI tools in the hands of every journalist and editor, allowing these folks to run their own data analysis or “vibe code” AI-powered widgets to help them in their jobs, or whether efforts should be top-down, with the management prioritizing projects.  Many called for a balanced approach, though there was no consensus on how to achieve it.

News outfits are also being cautious about building audience-facing AI tools. Many have begun using AI to produce bullet-point summaries of articles that can help busy and increasingly impatient readers. Some have built AI chatbots that can answer questions about a particular, narrow subset of their coverage—like stories about the Olympics or climate change—but they have tended to label these as “experiments” in order to help flag to readers that the answers may not always be accurate. Few have gone further in terms of AI-generated content. They worry that gen AI-produced hallucinations will undercut trust in the accuracy of their journalism. Their brands and their businesses ultimately depend on that trust.

This caution, while understandable, is itself a colossal risk. If news organizations themselves aren’t using AI to summarize the news and make it more interactive, technology companies are. People are increasingly turning to AI search engines and chatbots, including Perplexity, OpenAI’s ChatGPT, and Google’s Gemini and the “AI Overviews” Google now provides in response to many searches, and many others. Several news executives at the conference said “disintermediation”—the loss of a direct connection with their audience—was their biggest fear.  Cloudflare, which is also offering to help protect news publishers from web scraping, found that OpenAI scraped a news site 250 times for every one referral page view it sent that site.

So far, news organizations have responded to this potentially existential threat through a mix of legal pushback—the New York Times has sued OpenAI for copyright violations, while Dow Jones and the New York Post have sued Perplexity—and partnerships. Those partnerships have involved multiyear, seven-figure licensing deals for news content. (Fortune has a partnership with both Perplexity and ProRata.) Many of the execs at the conference said the licensing deals were a way to make revenue from content the tech companies had most likely already “stolen” anyway. They also saw the partnerships as a way to build relationships with the tech companies and tap their expertise to help them build AI products or train their staffs. None saw the relationships as particularly stable. They were all aware of the risk of becoming overly reliant on AI licensing revenue, having been burned previously when the media industry let Facebook become a major driver of traffic and ad revenue. Later, that money vanished practically overnight when Meta CEO Mark Zuckerberg decided, after the 2016 U.S. presidential election, to de-emphasize news in people’s feeds.

Executives acknowledged needing to build direct audience relationships that can’t be disintermediated by AI companies, but few had clear strategies for doing so. One expert at the conference said bluntly that “the news industry is not taking AI seriously,” focusing on “incremental adaptation rather than structural transformation.” He likened current approaches to a three-step process that had “an AI-powered Ferrari” at both ends, but “a horse and cart in the middle.”

He and another media industry advisor urged news organizations to get away from structuring their approach to news around “articles.” Instead, they encouraged the news execs to think about ways in which source material (public data, interview transcripts, documents obtained from sources, raw video footage, audio recordings, and archival news stories) could be turned into a variety of outputs—podcasts, short-form video, bullet-point summaries, or yes, a traditional news article—to suit audience tastes on the fly by generative AI technology. They also urged news organizations to stop thinking of the production of news as a linear process, and begin thinking about it more as a circular loop, perhaps one in which there was no human in the middle.

One person at the conference said that news organizations needed to become less insular and look more closely at insights and lessons from other industries and how they were adapting to AI. Others said that it might require startups—perhaps incubated by the news organizations themselves—to pioneer new business models for the AI age.

The stakes couldn’t be higher. While AI poses existential challenges to traditional journalism, it also offers unprecedented opportunities to expand reach and potentially reconnect with audiences who have “turned off news”—if leaders are bold enough to reimagine what news can be in the AI era.

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