We write the year 2026. For four years, AI has reigned supreme – and lots of news organisations have jumped on the bandwagon, caught on, thought deeply about how they, too, could make use of it.
So what do they (want to) use it for? While an overall picture of uses is hard to come by (due to the lack of representative data), thanks to my colleague Nic Newman we have a pretty good idea of what senior managers in news organisations around say that their organisations focus is with regards to AI.
I had a bit of fun, harmonising and comparing the data from 2022 (when Nic first asked this) and 2026, when he ran his most recent survey. The main finding: News executives now see AI as much more central to everyday news work than they did in 2022, especially for creating content and automating back-end tasks.
In many ways, AI has moved from being seen mainly as a useful support tool for news workers to something executives expect to matter across much more of the news business. Really the biggest change here is in “content creation”, which was relatively low in 2022 (and then framed as “robo-journalism,” a term which thankfully no one uses any longer). The emphasis on the same is much, much higher in 2026, 34 percentage points to be precise. I am not saying that everything that can be automated will be automated (although) but this demonstrates that not just the idea of using AI for content creation has become more acceptable, we also know this to be the case from lots of reported applications (and mishaps).
AI use in back-end automation also stands out, with executives now much more likely to say it is “very important”: read this as AI for tasks like tagging, transcription, copyediting, and workflow support, all of which has become a core priority in the search for low-hanging fruits to reap efficiencies.
Using AI for news-gathering has also risen, but not by very much, while commercial uses are basically unchanged, while AI use for recommendations and distribution appear lower than in 2022 – perhaps because this is an area where AI as in machine learning has been used for a long time.
[Caveat: This is not a perfect apples-to-apples comparison, because the question wording changed and the 2026 version explicitly mentions Generative AI.]
If you want to read the full reports: here is the 2022 version and here you can find the 2026 version – both highly recommended.