◆ E-COMMERCE · Marketing AI

Google's AI Mode returns products on 23% of shopping searches, and they are almost never the ones ranking today

Same catalogue, different shelf. Only 0.8% of products showed up on both surfaces for the same query on the same day.

Chandni Melwani

Chandni Melwani

Founder & Editor

Aug 4, 2026 · 2 MIN READ

A Google search results page open on a computer screen Global Photo: Nathana Rebouças / Unsplash

The News

Productrise, a company that tracks organic product visibility in Google Shopping, published a study on July 29, 2026 comparing standard Google search with AI Mode across more than 100,000 identical shopping queries and over two million listings, run side by side on the same day over 21 days in July, in the US and UK. Standard search returned at least one product on about 88% of those queries against about 23% in AI Mode. Where both returned products, standard search averaged 22.5 listings a page and AI Mode 4.3. Multiplied, that is roughly 95% less product visibility. Only about 0.8% of products appeared on both surfaces for the same query on the same day.

Know More

Search Google for neck cream and the page fills with a shoppable carousel. Ask AI Mode, the conversational surface inside Search, the same thing on the same day and it answers in prose, links out to a few review sites, and offers nothing to buy. That pair comes from a study published July 29 by Productrise, which ran more than 100,000 identical shopping queries across both surfaces over three weeks in July.

Standard search returned at least one product on about 88% of those queries. AI Mode managed about 23%. When products did appear, standard search showed 22.5 a page and AI Mode 4.3. Multiply the two and roughly 95% of the visibility is gone.

Google Ads’ own pitch for shopping inside AI Mode. It shows the experience Google is selling, not the product counts the study measured.

The smaller number is the one that should land. About 0.8% of products showed up on both surfaces for the same query on the same day, and both are fed by the same Shopping Graph, which Google says holds more than 60 billion listings, with more than two billion of them refreshed every hour. Availability is not the constraint here, selection is, and a feed that wins the carousel is not thereby winning the answer.

Two things keep this from being a verdict. Productrise sells Shopping visibility tracking, so the finding sits close to its product. And the study typed keywords rather than the follow-up questions AI Mode is built around, which is how most people reach it today but not the behaviour Google is designing for. Neither touches the overlap figure, and AI-referred shoppers still convert better than other traffic, while Shopify’s AI orders outran its AI traffic last quarter. The shrinking shelf may be worth more per slot than the one it replaced.

#Google#AI Mode#Google Shopping#Shopping Graph#SEO#Product Feeds#E-commerce

Frequently Asked Questions

Does ranking in Google Shopping carry over to AI Mode?

On this data, barely. About 0.8% of products appeared on both surfaces for the same query on the same day, so a strong carousel position is close to no evidence of appearing in the AI Mode answer for the same search.

Is 95% the drop in traffic?

No. It measures product listings displayed, not clicks or orders. Fewer slots can still be worth more per slot, and AI-referred shoppers have been converting better than other traffic.

What can a merchant act on now?

Measurement first. Google announced a Merchant Center report in May 2026, AI Performance Insights, for tracking brand performance inside AI Mode, though it is still rolling out country by country. It has also published Merchant Center attributes marked for conversational surfaces. Both are closer to checkable than the ranking logic behind the selection.

Chandni Melwani

Chandni Melwani

Chandni Melwani is the founder and editor of New in AI, covering AI agents, M&A, and enterprise adoption. She holds a Master's in Management of Artificial Intelligence from Queen's University and brings a practitioner's perspective from her work in Data and AI leadership.

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