Google AI Mode vs. Product Carousel: Price Differences Explained

Recent analysis from Productrise reveals a significant disconnect between Google’s AI Mode and the standard Popular products carousel, highlighting that these two interfaces rarely feature the same inventory or pricing structures. While consumers might expect consistency across Google’s search ecosystem, data indicates that when products do overlap, the primary seller is often different. This divergence suggests that AI-generated shopping results operate on distinct logic than traditional organic listings, potentially impacting how merchants optimize their visibility.

Minimal Inventory Overlap Between Interfaces

The extent of shared inventory between the two result types is surprisingly low. According to tracking data collected by Productrise, only 1.28% of products appearing in the popular carousel also showed up in AI Mode for identical searches conducted on the same day. This metric was derived from a rigorous monitoring period spanning August 9 to August 31, 2026. During this window, Productrise analyzed over 2 million product listings across more than 100,000 regular search results and corresponding AI Mode responses in both the US and UK markets.

The methodology involved executing parallel product-specific queries in both modes simultaneously. In standard search, the focus remained strictly on the Popular products carousel, excluding other modules like “Related searches” or “People also ask.” Conversely, AI Mode results were evaluated based on the product listings embedded within its narrative answers. Matching was achieved using Google’s unique product ID, allowing for precise comparison of the first-listed offer’s seller and price point on each side. It is important to note that these queries primarily reflected products already monitored on Productrise’s platform rather than a random sample of all Google searches.

When both systems returned results for the same query, the volume disparity was stark. The traditional carousel displayed an average of 27.8 products, whereas AI Mode presented just 3.9. This limited selection in AI Mode means that even if a product exists in the broader index, its chances of being featured in the AI-generated answer are significantly lower than securing a spot in the conventional carousel.

Divergent Sellers and Pricing Structures

For the small fraction of products that did appear in both result types, the offers themselves were frequently inconsistent. In nearly half of these overlapping cases (49.6%), the merchant listed first in AI Mode differed from the one leading the carousel. This shift in vendor often coincided with changes in pricing, suggesting that AI Mode may prioritize factors beyond mere availability or lowest cost.

Price discrepancies were notable among the matched items. Prices differed on 38.1% of the products found in both places. When a difference occurred, AI Mode displayed the higher price 68.4% of the time. Across all matched products, including those with identical prices, the average price in AI Mode was 21.6% higher than in the carousel. The median difference where AI Mode was more expensive stood at 22.2%, while the average difference reached 88.5%. Productrise attributes some of this extreme average inflation to outliers, such as comparing new items in AI Mode against used goods in the carousel. However, even when AI Mode offered lower prices, the median discount was modest at 7.8%.

Hugo Huijer, founder of Productrise, interpreted these patterns to suggest that “the cheapest price is less of a factor in AI Mode,” implying that other variables, such as detailed feed data or brand authority, may influence selection. This contrasts with the traditional e-commerce mindset where price competitiveness is paramount.

Merchant Implications and Data Limitations

The lack of alignment between AI Mode and the carousel presents a strategic challenge for retailers. A merchant might dominate the traditional carousel yet remain invisible or secondary in AI Mode, effectively competing against themselves for consumer attention. Currently, Google’s Merchant Center AI performance insights report provides metrics on share of voice for brands in AI Mode but does not disclose specific seller identities or pricing data. This gap leaves advertisers unable to verify which competitor is winning the prime real estate in AI-driven answers.

Furthermore, the data captures only what is visually presented on the screen, offering no insight into user clicks or final purchase decisions. Shoppers can still click through to view alternative sellers and compare prices, meaning the initial AI recommendation is just one entry point in a larger decision-making process.

Google responded to Futurism on September 2, stating:

“While we haven’t verified the accuracy of the claims in this report, all shopping results on Google Search, including AI Mode and the search results page, are powered by the same data source: our Shopping Graph. Shoppers can easily click into a product listing to compare prices for that product across retailers and choose the best option for them.”

Despite Google’s assertion of a unified data source, the practical outcomes differ markedly. For businesses aiming to maximize exposure, this divergence underscores the need to monitor AI Mode performance separately from traditional search rankings. As AI Mode becomes increasingly accessible via single-click interactions in Chrome and search bars, understanding its unique selection criteria will be crucial for maintaining competitive visibility.