Google Shopping AI Mode: 2026 Ad Changes, Price Gaps & Seller Shifts

Google Shopping in 2026 is undergoing a fundamental transformation driven by AI Mode, creating new challenges and opportunities for retailers. The key change is that AI-generated shopping results increasingly diverge from traditional search results, with different prices, sellers, and ad placements that complicate measurement and strategy.

As Google integrates Gemini models into Search and tests new ad formats, the shopping experience is splitting into two parallel realities. Retailers must understand these shifts to optimize their visibility and performance in both traditional and AI-driven shopping results.

What Is Google AI Mode and How Does It Change Shopping?

Google AI Mode is a search experience powered by large language models that generates conversational, AI-crafted answers to user queries. Instead of showing a traditional list of links and shopping carousels, AI Mode synthesizes information from across the web to provide direct, comprehensive responses.

For shopping queries, this means AI Mode often recommends products and sellers based on its analysis of available information, rather than simply echoing the standard shopping results. This creates a significant divergence that retailers need to understand.

AI Mode Product Prices Average 21.6% Higher

A study found that products displayed in Google's AI Mode often show different prices and sellers compared to traditional search results. Specifically, AI Mode prices average 21.6% higher than those in standard results. This discrepancy suggests that AI Mode may be prioritizing factors other than price, such as brand reputation, product descriptions, or seller ratings, when making recommendations (techwyse.com).

For shoppers, this means the "best" price may not be the one shown in AI Mode. For retailers, it highlights a potential disconnect between what they offer and what AI Mode surfaces.

Seller Mismatch: Only 1.28% Overlap with Traditional Carousel

Tracking data reveals that Google AI Mode rarely mirrors the "Popular products" carousel in standard search results. The study found only 1.28% overlap between products shown in AI Mode and those in the standard shopping carousel. Additionally, the lead seller—the first seller shown—differs nearly half the time between the two experiences (indexlab.ai).

This low overlap means that a product highly visible in traditional results may be completely absent from AI Mode. Retailers who rank well in standard shopping may find themselves invisible in AI-generated answers.

Why Pricing Plays a Different Role in AI Mode Selection

The data suggests that pricing may be less of a factor in AI Mode's product selection. While traditional shopping results often prioritize competitive pricing, AI Mode appears to use a broader set of criteria, including product reviews, brand authority, content quality, and other signals.

This shift has significant implications:

Price-sensitive shoppers may miss better deals if they rely solely on AI Mode.
Retailers with competitive prices may not see expected visibility in AI answers.
Measurement becomes harder—standard reporting tools may not capture AI Mode performance accurately.

Google has not publicly detailed the exact algorithms behind AI Mode's product selection, leaving retailers to infer patterns from observed data.

Google Tests New Shopping Ad Placements Inside AI Mode

Google is actively testing two new shopping ad placements directly within AI Mode results. These placements include an inline product carousel, which appears within the AI-generated answer itself, rather than in a separate sidebar or below the results.

According to reports, Google has not provided specific reporting dimensions in Google Ads for these new placements, making it difficult for advertisers to measure their performance (ppc.land).

What This Means for Advertisers

The lack of transparent reporting creates a "black box" for advertisers. Without dedicated metrics, it's challenging to:

Determine which ads appear in AI Mode placements.
Measure click-through rates and conversions from these placements.
Optimize bids and budgets for AI Mode-specific performance.

This opacity may change as Google refines the feature, but for now, advertisers must work with incomplete data.

The 'Reverse Crocodile Effect': Shopping Ad Performance Shifts

Data suggests that since the introduction of AI Overviews, Google Shopping ad impressions have declined while click-through rates have increased. This phenomenon has been dubbed the "reverse crocodile effect" (seroundtable.com).

The name plays on the "crocodile effect"—a term sometimes used to describe situations where fewer impressions but higher engagement lead to net-neutral outcomes. In this case, the shifts may reflect changes in how shopping ads are displayed and when users see them.

Fewer Impressions, Higher CTR: The Trade-Off

Metric	Traditional Trends	With AI Overviews
Ad impressions	Stable or growing	Declining
Click-through rates	Modest	Increasing
Overall clicks	Consistent	Potentially stable

This table is illustrative based on the observed trends. The higher CTR may indicate that users who see shopping ads in AI-influenced results are more intent-driven, but the reduced impressions mean fewer total opportunities.

For retailers, this means focusing on conversion rate optimization for the clicks they do receive, rather than relying on high impression volumes.

Google Search Redesign and Business Profile Changes

Beyond Shopping, Google Search is undergoing a broader redesign. Recent updates include changes to how Business Profiles display post views, which can affect local shopping and discovery (searchenginejournal.com).

While not directly a shopping feature, these changes impact the overall search landscape in which shopping results appear. Retailers should monitor these updates as they can influence visibility and click-through rates across all result types.

Search Ranking Volatility and Its Impact on Shopping

Google has seen notable search ranking volatility, including a period of fluctuations around September 2026. Reports indicate that a search update on September 4th was later reverted on September 13th, causing confusion among site owners (seroundtable.com).

Such volatility can affect shopping visibility, especially for retailers who rely on organic traffic. While Shopping ads and organic results are separate systems, changes in overall SERP layout can influence how prominently shopping features appear.

Google Search Ranking Volatility Heats Up

Another report notes that search ranking volatility heated up on September 15th, coinciding with other updates (seroundtable.com). This suggests that Google is actively iterating on its algorithms, which may introduce further changes to shopping results.

Google Tests Blue 'More' Link in Shopping Results

In a related development, Google is testing a blue "More" link in shopping results, potentially allowing users to expand their view of products or sellers (seroundtable.com).

This small UI change could have implications for how many products users see and how they interact with shopping results. Retailers should watch for this feature's rollout and consider how it affects user behavior.

Gemini 3.8 Live and Its Role in Search

Google recently released Gemini 3.8 Live, a new model powering Search Live on the Google app. This integration enables more fluid, real-time, and multilingual conversational AI experiences with web links for deeper dives (searchengineland.com).

While primarily focused on general search, this technology underpins AI Mode and other AI-driven features, potentially influencing how shopping queries are handled.

How Gemini 3.8 Live Affects Shopping

As Gemini models become more capable, they are likely to improve their understanding of product attributes, user intent, and context. This could lead to more accurate recommendations but also greater divergence from traditional ranking signals.

Retailers should adapt by ensuring their product data is well-structured and rich with details that AI models can parse, such as:

Clear product titles and descriptions.
High-quality images and videos.
Comprehensive attributes (size, color, material, etc.).

Google Search Tests Blue 'More' Link in Shopping Results

A separate report confirms that Google is testing this blue "More" link specifically within shopping results. This test could indicate Google's efforts to improve the shopping experience by offering more options to users (seroundtable.com).

Image Thumbnail Updates and Shopping

Google also noted that slow image thumbnail updates are normal in Search. This can affect shopping results that rely heavily on product images, potentially causing mismatches between what's displayed and what's available (seroundtable.com).

What Retailers Should Do Now

As Google Shopping diverges into AI Mode and traditional results, retailers need to adopt a multi-pronged approach:

Track both experiences: Use tools that capture visibility in both AI Mode and standard results.
Optimize for AI understanding: Ensure product data is rich, structured, and semantically clear.
Monitor ad performance closely: Since new AI Mode ad placements lack reporting, manually track clicks and conversions where possible.
Focus on CTR and conversion: With fewer impressions, higher CTR, and better conversion rates become more critical.
Stay agile: Google's algorithm updates are frequent, so maintain flexibility in strategies.

The Bottom Line

Google Shopping is entering a new era defined by AI-driven divergence. The 21.6% price gap, 1.28% seller overlap, and new ad placements signal a significant shift in how products are discovered and purchased. Retailers who embrace these changes—by optimizing for AI Mode, adapting their ad strategies, and monitoring performance across both realities—will be better positioned to succeed in 2026 and beyond.

The landscape is evolving rapidly, and staying informed is the first step to thriving in this new shopping paradigm.