Google AI Mode and AI Overviews: what do they mean for fashion retail traffic?

Google AI Mode and AI Overviews mean that fashion retailers will receive fewer clicks from informational searches, because Google increasingly answers questions such as what to wear or how a fabric behaves directly on the results page. At the same time Google is building shopping into AI Mode, from product comparisons to virtual try-on and checkout, so competition for the remaining clicks moves inside Google's own interface. Retailers with strong product data and unique content are better placed than those relying on generic guides.

What are AI Overviews and AI Mode?

AI Overviews are AI-generated summaries shown above or among classic results when Google judges they add value. AI Mode is a separate, conversational search experience. Google announced at its I/O conference on 20 May 2025 that AI Mode would start rolling out to everyone in the United States, and said on 7 October 2025 that it was launching in more than 35 new languages and over 40 new countries and territories, making it available in over 200 countries and territories, including many across Europe.

Both features may use what Google calls query fan-out: "breaking down your question into subtopics and issuing a multitude of queries simultaneously". Google says this lets it show a wider and more diverse set of links than classic search.

How much traffic do AI summaries take away?

The most cited independent measurement comes from Pew Research Center. It analysed the Google searches of 900 US adults in March 2025, 68,879 searches in total. An AI summary appeared on 18% of them. On pages with a summary, users clicked a traditional result on 8% of visits, against 15% on pages without one. They clicked a link inside the summary on 1% of visits, and ended their browsing session on 26% of visits with a summary, against 16% without.

The data is US-only and from early 2025, before the wider AI Mode rollout, and it covers all topics rather than fashion. It still gives retailers a reasonable planning assumption: where an AI summary appears, expect click-through to fall substantially.

Retailers should also watch the second-order effect. When fewer visitors arrive from informational searches, remarketing audiences, newsletter sign-ups and first-party data collected from those visits shrink as well. The loss is therefore not only in sessions but in the pool of prospects that later convert through other channels.

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How is AI search changing the way shoppers find fashion?

Which fashion searches are most affected?

This is an assessment, not a measurement. Each retailer should test it against its own Search Console data by grouping queries into these types and comparing click-through rates over time. Google states that AI Overview and AI Mode traffic is included in the Web search figures there.

What is Google building into AI Mode for shopping?

Google announced AI Mode shopping features on 20 May 2025, built on its Shopping Graph, which it said contains more than 50 billion product listings, with about 2 billion refreshed every hour. The announced features include:

• Browsing and filtering with a panel of products that updates as the shopper refines the request.
• Price tracking where shoppers set size, colour and a maximum price and receive an alert.
• Virtual try-on for shirts, trousers, skirts and dresses, using a full-length photo of the shopper, launched in Search Labs in the US.
• Agentic checkout where Google adds an item to the merchant's cart and completes payment with Google Pay after the shopper confirms, announced for US listings.

For fashion retailers, this means that a growing part of discovery, comparison and even purchase can happen within Google. Product feeds, prices, size availability and images become the competitive surface.

What should fashion retailers do in 2026?

1. Segment Search Console queries by intent and track click-through rate trends for informational versus product queries.
2. Shift content investment from generic advice towards unique assets: fit data, detailed materials, original imagery and verified reviews.
3. Audit Merchant Center feeds and product markup for complete colour, size, material, gender and availability data.
4. Keep important facts in text on the page; Google lists text content, crawlability and up-to-date Merchant Center data among the fundamentals for AI features.
5. Plan budgets on the assumption that some informational traffic will not return, and measure the business by revenue and margin rather than sessions.

Read also

How to audit your fashion brand's visibility in ChatGPT, Gemini and Perplexity

Is there an upside for fashion retailers?

Brand building also gains weight. When the shortlist is composed by an assistant, being a brand the shopper already knows and searches for by name is a defence against disappearing into a generic answer. Investment in brand search, CRM and owned channels such as apps and newsletters reduces dependence on informational search traffic that may not return.

There can be. Google argues that fan-out surfaces a more diverse set of links, which may give specialist retailers a chance to be cited for specific sub-questions. Shoppers who arrive after an AI-assisted comparison may also be further along in their decision. Neither benefit is guaranteed, and the evidence so far points to fewer clicks overall. Retailers should treat AI Mode as a channel with its own rules, invest in the data it reads, and avoid both panic and complacency.