A 2026 Productrise study reported by Search Engine Journal found very little overlap between products shown in Google's Popular products carousel and AI Mode for the same product focused searches. Even when the same product appeared in both, the first seller and displayed price could differ.
The lesson for ecommerce teams is clear: visibility in regular Google shopping surfaces does not guarantee equivalent visibility in AI Mode. Brands need to monitor AI shopping as a separate discovery environment.
What did the Google AI Mode shopping study find?
Productrise monitored more than 2 million product listings across more than 100,000 regular Search results and AI Mode responses between August 9 and August 31, 2026, according to Search Engine Journal.
The reported average daily overlap was 1.28% between products in the Popular products carousel and AI Mode for the same query and day. Among products appearing in both, the first seller differed 49.6% of the time. Prices differed for 38.1% of matched products, and among those price differences AI Mode showed the higher price 68.4% of the time.
Google told Futurism that it had not verified the accuracy of the report's claims and said both experiences use the same Shopping Graph. Read the Search Engine Journal analysis.
Why can the same Shopping Graph produce different results?
The study does not establish why AI Mode and the regular carousel select different products or sellers. That is an important limitation.
What marketers can observe is that the surfaces behave differently. AI Mode displayed fewer products per query in the dataset, so selection becomes more concentrated.
When an interface shows only a small set of recommendations, being included can matter more than simply being present somewhere in a long product carousel.
What does this mean for ecommerce visibility?
Ecommerce teams should stop assuming that strong Google Shopping visibility automatically transfers into AI Mode. The AI interface needs its own monitoring.
For priority products, compare:
- Whether the product appears in regular Search
- Whether it appears in AI Mode
- Which seller is shown first
- Which price is displayed
- What product attributes are highlighted
- Which competitors appear instead
This creates an AI merchandising question in addition to a classic SEO and Shopping question.
Should brands compete only on price?
No. The study cannot prove which ranking factors cause AI Mode selection, and the source explicitly notes that it does not reveal why the two surfaces choose different products or sellers.
Brands should therefore avoid simplistic conclusions such as “lower price wins” or “richer feed data guarantees AI Mode.” Instead, make sure product data is accurate, complete and consistent, then measure what actually appears.
The strategic advantage comes from learning how your own catalog behaves rather than extrapolating too much from one dataset.
How should product pages support AI shopping?
Product pages should give both Google and buyers reliable information about the item. That includes product identity, specifications, variants, availability, pricing context, shipping or policy information and useful descriptions.
The page should also answer questions that appear during comparison. If AI Mode presents only a few products, clear differentiation can help the user understand why one option fits better.
A broader AI visibility audit can connect product page quality with crawl access, authority and the way AI systems describe the brand.
What should retail teams monitor next?
Watch for changes in Merchant Center AI reporting, seller visibility, AI Mode product selection and the relationship between product feed quality and AI presentation.
Also track business outcomes. A product appearing in AI Mode is useful only if it contributes to qualified traffic, conversion, brand demand or assisted sales.
The emergence of AI shopping makes SEO, feed management, product content and analytics more connected. Teams that keep those functions separate may struggle to explain why visibility changes.