What Google's AI overviews mean for SEO

AI SEO and Google AI Overviews: what's really changing in search

AI SEO is no longer a theoretical discussion about Google's future. It's already a practical issue for any e-commerce owner who relies on organic traffic, category pages, product pages and informational content to bring customers to their site. With Google AI Overviews, the search engine doesn't just display ten blue links and a few rich results. It produces a concise response at the top of the results page, synthesizing information from multiple sources and suggesting links it deems useful for further reading. This means that visibility in SEO is no longer measured only by whether a page is ranked in the first place, but also by whether the brand can be recognised, mentioned and leveraged within AI-generated answering environments. See also: Digital Marketing & SEO, business automation & AI, website construction, e-shop construction.

HubSpot's article on what AI Overviews mean for SEO is along these lines: marketers shouldn't view the change as the end of organic traffic, but as a shift in the way people discover, evaluate and trust information. For an e-shop, the difference is critical. A user searching for “best running shoes for beginners”, “how to choose a child car seat” or “which face cream is suitable for oily skin” can get a complex AI answer before they even visit a site. If your content is clear, well-researched, expert and useful, you stand a good chance of being in the chain of trust that feeds the answer. If your content is generic, copied from vendors or written only for keywords, you risk being left out of the new search experience.

The scale of change is large. Google announced that AI Overviews exceeded 1 billion monthly users in 2024 and later reported that they are used by over 1.5 billion monthly users. This does not mean that every search generates AI Overview, nor does it mean that every industry is affected in the same way. But it does mean that AI SEO is moving from the monitoring stage to the operational adaptation stage. As shown in the chart below, adoption of AI Overviews has grown rapidly at the user level, which explains why SEO, content and e-commerce teams need to rethink their priorities.

Why AI Overviews affect clicks, content and trust

The biggest concern around AI Overviews is the potential decrease in clicks. If the user gets a satisfactory response directly to Google, they may not visit any results. The phenomenon of zero-click searches is not new, as featured snippets, knowledge panels and local packs had already changed user behavior. The difference is that AI Overviews can answer more complex queries, compare options, explain steps and combine information from different sources. For an e-commerce brand, this moves part of the purchase decision higher up the SERP before the user enters the store.

Pew Research Center data shows why professionals can't ignore this change. In a Google usage survey, when an AI summary was displayed, users clicked on a traditional result in 8% of visits, compared to 15% when no AI summary was displayed. At the same time, users terminated the search without another click more often when AI summary was present, at 26% versus 16% without AI summary. This does not prove that every site will lose traffic in the same way, but it does reflect a clear behavioural shift: the top of the search becomes more answering and less merely navigational.

The practical conclusion for e-shop owners is that organic traffic needs to be evaluated more qualitatively. You may see fewer clicks on informational queries, but the clicks that come after an AI response may be more mature because the user has already done a first filtering. Therein lies the opportunity: design content that doesn't just chase traffic, but answers real buyer questions, demonstrates expertise, and drives the user to a clean next action, such as product comparison, sizing, purchase, registration, or contact.

The increasing occurrence of AI Overviews in more queries confirms that the change is not limited to a few test searches. According to a study by Semrush, the percentage of queries that triggered AI Overviews increased from 6,49% in January 2025 to 13,14% in March 2025. This trend is important for AI SEO because it shows that Google is gradually expanding the type of queries to which it finds an AI-generated answer useful. For e-commerce categories with many comparison, research and selection queries, the potential for influence is even greater.

What AI SEO means for e-commerce brands

AI SEO is the evolution of SEO strategy so that the content, technical infrastructure and credibility of a brand can be understood by both traditional ranking algorithms and generative engine optimization systems. The term does not mean abandoning the basics of SEO. Rather, we make them more rigorous: clean architecture, fast loading, technical health, properly canonical, structured data, readable content, strong internal linking and true subject matter expertise. The difference is that now the content must be able to act as a credible source of response, not just a page targeting a keyword.

For an e-shop, the traditional approach of “one category, a few lines of SEO text and product descriptions from the supplier” is not sufficient. AI Overviews tend to favor content that clearly answers intent, explains decision criteria, presents experience, and reduces uncertainty. If you sell vacuum cleaners, it's not enough to have a category page with filters. You need guides for floor types, noise, suction power, suction power, autonomy, parts, common buying mistakes and comparison scenarios. If you sell cosmetics, it's not enough to repeat “moisturize” and “shine”. You need informed answers about skin types, ingredients, usage, contraindications, routines and expected results.

The concept of E-E-A-T, i.e. Experience, Expertise, Authoritativeness and Trustworthiness, becomes more important in this environment. Google does not use E-E-A-T as a simple single ranking factor, but the framework describes what it considers quality and trustworthy content. In practice, an e-commerce site needs visible evidence of expertise: who writes the guide, why they have knowledge of the subject matter, what data they use, how advice is linked to real products, what return and warranty policies enhance trust, and how to avoid over-promising. In industries such as health, supplements, insurance, financial or children's products, documentation is not a luxury. It is a commercial defence.

Step-by-Step Customization Guide for AI Overviews

Implementation steps for content, technical SEO and measurement

Step 1: Map the queries that bring in revenue and not just traffic. Start in Google Search Console and extract queries with impressions, clicks, CTR and average position. Divide them into three groups: transactional, commercial investigation and informational. Transactional queries such as “buy lenovo laptop” remain critical for categories and products. Commercial investigation queries like “best laptop for students” are the most vulnerable to AI Overviews but also the most valuable for gaining trust. Informational queries such as “what is oled display” can support content marketing and internal linking. Priority should be given to topics where the brand has products, margin and real knowledge.

Step 2: Analyze the SERP as a response experience, not a list of links. For each important keyword, check if AI Overviews, featured snippets, People Also Ask, videos, forums, shopping results or comparison modules appear. Record which formats appear, which queries are repeated and which competitors are mentioned. If an AI Overview displays specific selection criteria, those criteria should be present in your own content, but with more precision, better structure and more useful commercial context. Don't copy Google's answer. Create the best page a buyer would want to consult before paying.

Step 3: Create thematic clusters that link guides, categories and products. A strong AI SEO model for e-commerce doesn't rely on isolated articles. You need a cluster, for example “mattress selection”, that includes a buying guide, articles on hardness, materials, sleeping posture, frequently asked questions, category pages and selected products. The internal linkage should be logical: the guide helps the user understand the problem, the category gives options and the product pages help the user decide. This increases thematic consistency, improves the user experience and makes it easier for search engines to understand your depth.

Step 4: Write answers with clear structure and factual value. Each important page should quickly answer the key question, but also provide depth for anyone who wants to compare. Use short explanatory introductions, comparison tables where appropriate, FAQ sections, usage examples, warnings and practical criteria. Long-tail keywords should be naturally embedded within questions and answers, not piled at the bottom of the page. Conversational search leads users to more natural formulations, so content should speak like an expert advisor, not a product catalogue.

Step 5: Enhance structured data and technical readability. Add Product, Offer, AggregateRating where there are actual ratings, FAQPage where questions are actually visible on the page, BreadcrumbList for navigation and Organization schema for brand elements. Make sure Google can crawl and render key information, that pages don't hide critical content behind scripts, and that titles, meta descriptions and headings clearly capture the topic. Structured data doesn't guarantee display in AI Overviews, but it helps engines understand entities, relationships, and commercial information.

Step 6: Add evidence of trust. At the brand level, this means clear “About Us” pages, contact information, return policies, payment methods, guarantees, real reviews and references to certifications. At the content level, it means writers or reviewers with relevant experience, update dates, resources, product trials where possible, and a clear distinction between facts, advice and trade recommendations. E-E-A-T is not built with a signature at the end. It is built consistently throughout the customer journey.

Step 7: Measure differently. AI SEO requires you to track not only rankings and clicks, but also visibility into SERP features, CTR changes by intent type, conversion rate from organic sessions, assisted conversions, branded searches and engagement with buying leads. If clicks on informational articles decrease but sales from users landing in categories increase, the strategy can work. Conversely, if you're losing impressions, clicks and revenue on commercial queries, you need content upgrades, technical testing and possibly better differentiation against competitors.

Practical priorities for the next day of SEO

The first priority is to stop the production of generic content without knowledge ownership. AI Overviews can easily summarize generic information. But they cannot so easily replace the experience of a brand that knows its products, has data from customers, understands pre-purchase objections and can give practical advice. If your page says the same thing as ten competitors, there's no strong reason to choose it as a source. But if it offers concrete examples, comparisons, real answers and clear commercial guidance, it increases your chances of gaining visibility and trust.

The second priority is the connection between SEO and merchandising. Many e-shops treat the blog as a separate channel from sales. In the new environment, this is a mistake. A shopping guide should be linked to filters, best sellers, bundles, available inventory and profit margins. The SEO team needs to know which products the business wants to promote, which ones have frequent returns, which ones need more pre-purchase education and what questions customers are asking support. This information creates content that is useful to humans and understandable by the engines.

The third priority is to adapt to the logic of the search generative experience. Users will ask increasingly complex questions, such as “I want a gift for a 35-year-old woman who loves skincare but has sensitive skin” or “which desk is suitable for a small room and telecommuting”. These queries are not answered well by simple product pages. They require content that understands circumstances, constraints and choices. AI SEO is therefore not just technical optimization. It's better understanding of the customer.

The fourth priority is to protect brand demand. The more responses that appear directly on Google, the more important it becomes that people search for you by name. The brand acts as a trust anchor. Invest in email, social media, remarketing, trusted content, partnerships and great post-purchase experience. SEO should not work in isolation from branding. If the audience recognizes your brand, they are more likely to choose your link even within a more crowded and responsive SERP.

Ultimately, AI Overviews don't eliminate the need for SEO. They eliminate the comfort of mediocre SEO. E-commerce brands that continue to rely on thin pages, repetitive product descriptions and opinion-free articles will be squeezed. Those that invest in technical clarity, E-E-A-T, useful guides, structured data, commercial thinking and continuous measurement will have a better chance of showing up where decisions are made. AI SEO is, in effect, an invitation to make content more useful, more accurate and closer to the real customer.

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