AI Overviews Now Appear on 14% of Shopping Queries: What It Means for Your Ads

A new study from Visibility Labs analyzed 20.9 million shopping keywords and found that Google's AI Overviews now appear on 14% of them — up 5.6x from just 2.1% in November 2024. For ecommerce advertisers who rely on Google Shopping for product visibility, this is a seismic shift in how search results pages are structured. AI-generated summaries are claiming prime real estate at the top of SERPs, and the rate of expansion shows no signs of slowing down.

If you're running Shopping campaigns, this affects you directly. AI Overviews change what shoppers see before they ever scroll to your product listings. They reshape click-through rates, alter the competitive landscape, and create a new category of visibility that your current bidding strategy doesn't account for. As Search Engine Land reported, this is one of the most significant changes to shopping SERPs since the introduction of free listings in 2020.

Key Findings from the Visibility Labs Study

The study's headline number — 14% of shopping queries showing AI Overviews — is striking on its own, but the breakdown by query type reveals a more nuanced picture. Not all shopping queries are equally affected, and understanding the distribution is critical for adjusting your strategy.

The core data points from the study:

• 14% overall presence across 20.9 million shopping keywords — this is the blended average across all query types and product categories.
• 5.6x growth from the 2.1% baseline measured in November 2024. This acceleration means Google has been aggressively expanding AI Overview triggers on commercial queries over the past 16 months.
• 83% of "best [product]" queries now show AI Overviews. This is the highest-penetration category by far. Queries like "best running shoes 2026" or "best wireless earbuds under $100" are almost guaranteed to have an AI Overview at the top.
• 35–45% of review and comparison queries trigger AI Overviews. Searches like "airpods vs galaxy buds" or "dyson v15 review" fall into this bucket. Shoppers in the comparison phase are seeing AI-generated summaries before they reach any traditional result.
• 13–14% of pure transactional queries are affected. These are the "buy nike air max" and "order macbook pro" searches where intent is clearly purchase-driven. While the rate is lower than research queries, 13–14% is still meaningful — and growing.
• ~8% of brand + product queries show AI Overviews. Searches like "apple macbook pro m4" or "samsung galaxy s26 ultra" are the least affected, likely because Google treats branded navigational queries differently.

Which Query Types Are Most Affected

The distribution across query types follows a clear pattern: the more research-oriented the query, the more likely it is to trigger an AI Overview. Understanding this pattern helps you decide where to shift budget and where your existing strategy still holds.

Informational: "Best [Product]" Queries

At 83% penetration, informational shopping queries are effectively an AI Overview-first experience. When a shopper searches "best robot vacuum 2026," they see a multi-paragraph AI-generated summary with product recommendations, pros and cons, and price ranges before they see a single Shopping ad or organic listing. This is the category where the SERP has changed most dramatically.

For advertisers, this means your Shopping ads on "best" keywords are being pushed below a large block of AI-generated content. The shopper may form opinions and narrow their consideration set before they ever see your product listing. If your product is cited in the AI Overview, you get a visibility boost that no amount of bidding can buy. If it isn't, you're fighting for attention in a diminished space below the fold.

Comparison: Head-to-Head Queries

Comparison queries like "airpods vs galaxy buds" or "roomba vs dyson" trigger AI Overviews 35–45% of the time. These queries represent shoppers who have narrowed their options and are looking for the deciding factor. The AI Overview typically presents a structured comparison — feature tables, price differences, and use-case recommendations — that directly competes with the comparison content your Shopping ads and landing pages provide.

This category is particularly relevant for brands competing in crowded product spaces. If Google's AI consistently recommends your competitor's product in these comparison summaries, your Shopping ads are fighting an uphill battle even before the shopper clicks.

Transactional: High-Intent Purchase Queries

Pure transactional queries — "buy nike air max 90," "order dyson airwrap" — show AI Overviews at 13–14%. This is the lowest rate among intent types, which makes sense: Google recognizes that shoppers with clear purchase intent want to transact, not read summaries. But 13–14% is still one in seven queries, and the trend is upward.

The transactional category is where most ROAS-focused Shopping budgets are concentrated. For now, these queries remain the safest from AI Overview disruption. But if the growth rate from the past 16 months continues, even transactional queries could see significantly higher AI Overview penetration by late 2026.

Brand-Specific: Navigational Queries

Brand + product queries like "apple macbook pro m4" or "samsung galaxy s26 ultra" show AI Overviews only about 8% of the time. These queries have strong navigational intent — the shopper knows exactly what they want and often which brand they want it from. Google's approach here seems to be preserving direct brand-to-consumer connections rather than inserting AI intermediation.

For brand advertisers, this is good news in the short term. Your branded Shopping campaigns are the least disrupted. However, the 8% figure is still higher than zero, and for non-dominant brands competing on branded queries of market leaders, even occasional AI Overview appearances can shift share of voice.

Impact on Shopping Ads and Organic Listings

The mechanical impact of AI Overviews on Shopping SERPs is straightforward: they push everything else down. A typical AI Overview on a shopping query takes up 300–500 pixels of vertical space — sometimes more when it includes product cards, comparison tables, or citation links. That's space that was previously occupied by your Shopping ads or free listings.

CTR compression is real. When Shopping ads drop from position one to effectively position two (below the AI Overview), click-through rates decline. Early industry data suggests CTR reductions of 15–30% on queries where AI Overviews appear, though the impact varies by product category and how prominently the AI Overview features specific products.

Products cited in AI Overviews get a visibility boost. This is the flip side. When an AI Overview mentions your product by name — "the Nike Pegasus 41 is the best all-around daily trainer" — that's premium placement you didn't pay for. It builds credibility and primes the shopper to look for your listing when they do scroll. The challenge is that there's no direct lever to control whether your product gets cited. It depends on your product's review profile, structured data quality, and content presence across the web.

Organic free listing visibility takes a hit. If you've been investing in organic Shopping performance through structured data and feed optimization, AI Overviews add another layer of content above your organic listings. The good news is that products with excellent structured data are more likely to be cited within the AI Overview itself, partially offsetting the positional loss.

What You Can Do About It

AI Overviews aren't going away. The 5.6x growth over 16 months signals that Google is committed to expanding this feature across commercial search. Rather than waiting for the next data point, here are concrete actions you can take now to adapt your Shopping strategy.

1. Audit Your Keyword Exposure

Start by understanding how much of your current Shopping traffic comes from queries where AI Overviews now appear. Pull your search terms report and classify your top queries by type — informational ("best"), comparison ("vs"), transactional ("buy"), and brand-specific. Cross-reference against the penetration rates from the Visibility Labs study to estimate your exposure.

If 40% of your traffic comes from "best [product]" queries, you know that 83% of those SERPs now have AI Overviews — meaning a significant portion of your impressions are below AI-generated content. Use product-level analytics to track whether CTR and conversion rates have shifted on these query types over the past quarter.

2. Optimize Product Content for AI Inclusion

Products that appear in AI Overviews tend to share certain characteristics: strong review profiles, complete structured data markup, and detailed product descriptions that answer common shopper questions. While there's no guaranteed formula, you can improve your odds.

• Structured data: Implement complete Product schema markup on your product pages, including price, availability, reviews (aggregate rating), brand, SKU/GTIN, and product attributes like color and size. The more structured data Google can parse, the more likely your product is to surface in AI-generated summaries.
• Reviews: Products with high volumes of authentic reviews are cited more frequently. If your review collection strategy is passive, consider actively soliciting reviews through post-purchase emails and loyalty program incentives.
• Product descriptions: AI models need clear, factual, and comprehensive descriptions to generate accurate recommendations. Move beyond marketing copy and include specific technical details, use cases, and comparison points. Optimize your product titles to be descriptive and keyword-rich.
• Feed completeness: Your Merchant Center feed is a primary data source. Use a feed intelligence tool to identify missing attributes and fill data gaps. Every empty field is a missed signal to both Shopping algorithms and AI models.

3. Shift Your Keyword Strategy

The data tells a clear story: transactional queries (13–14% AI Overview presence) and brand queries (~8%) are far less affected than informational queries (83%). If you're spending heavily on "best" and comparison keywords, consider reallocating some of that budget toward higher-intent transactional terms where your Shopping ads still have prime placement.

This doesn't mean abandoning "best [product]" keywords entirely. If your product is consistently cited in AI Overviews for those queries, maintaining bidding presence reinforces the AI recommendation with a visible ad below it. But if your product isn't being cited, you're paying for impressions in a diminished position. Review your search term performance data and adjust accordingly.

4. Diversify Beyond Search

AI Overviews are a search-specific change, but the broader trend they represent — AI intermediation between shoppers and products — extends across channels. Building presence on surfaces that AI can't displace is a long-term hedge.

• Meta Shopping ads: Facebook and Instagram product ads operate in a feed-based environment where AI Overviews don't exist. If you're not already running cross-channel, the feed optimization work you do for Google Shopping transfers directly to Meta catalogs.
• Agentic commerce: Google's Universal Commerce Protocol (UCP) and recent UCP expansion represent a future where AI agents don't just summarize products — they complete purchases. Early UCP adoption positions you for a commerce model where feed quality determines whether AI agents can transact with your catalog at all.
• Owned channels: Email, SMS, loyalty programs, and direct-to-consumer content are channels where your product visibility isn't mediated by AI summaries. The more you invest in direct customer relationships, the less dependent you are on any single search feature.

The Bigger Picture: Feed Quality Is the New SEO

AI Overviews on shopping queries are part of a larger transformation. Combined with Google's AI Overviews expansion, AI Mode, and the Universal Commerce Protocol, the message is clear: Google is building an AI-mediated shopping experience where product data quality determines visibility across every surface.

In the traditional Shopping model, your bid and budget determined how often your product appeared. Feed quality mattered, but it was one factor among many. In the AI-mediated model, feed quality is the foundation for everything — whether AI Overviews cite your product, whether AI agents can recommend it, whether agentic checkout can complete the sale. Incomplete feeds don't just lose a few positions in Shopping ads; they become invisible to AI systems entirely.

This is why the Visibility Labs data matters beyond its immediate tactical implications. The 5.6x growth from November 2024 to March 2026 isn't a blip — it's a trajectory. If the rate even partially continues, we could see AI Overviews on 25–30% of shopping queries by the end of 2026. Retailers who treat this as a feed quality and content strategy challenge — not just an advertising optimization problem — will be best positioned as the SERP continues to evolve.

The winners in this new landscape will be the advertisers who optimize their feeds obsessively, build review profiles that AI models trust, and diversify their commerce presence across channels. The data is telling you where things are heading. The question is whether you adjust now or wait until the next study shows 25%.

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