1 1. What is query fan-out? When a user enters a search query in AI Mode, Google does not send a single search query to its systems. Instead, it expands the original query into a whole series of related queries. This process is called “query fan-out.” Consider, for example, the question: “What is the best way to travel sustainably with children?” In AI Mode, Google translates this question into multiple underlying intentions, such as: What are sustainable transportation options? What are child-friendly travel destinations? How do you plan a sustainable family vacation? What are some tips for traveling with young children? Google searches for relevant pages and sources for each of these sub-questions. It then combines them into a single, clear AI answer.
2 2. Why is query fan-out important for SEO? Because it means that your page does not necessarily have to match the original search query exactly. If you have built up authority within a certain theme, there is a good chance that you will be mentioned in one of the fan-out search queries and thus still become part of the AI response. Topical authority is therefore becoming more important than ever. If your website: has multiple relevant pages on a particular topic, offers broad and in-depth content within that domain, demonstrates consistent quality and structure,… …then there is a good chance that Google will select your site more often within query fan-out. Your website will therefore not only be judged on a single page, but on the entire thematic ecosystem you have built up. In short: topical coverage will soon ensure visibility in AI Mode.
3 3. Context-sensitive response In addition to fan-out, AI Mode uses contextual interpretation. This means that the answer is not only based on keywords, but also on intention, sequence, and context. For example, if someone asks about “the best garden plants for shade,” the system also knows that humidity, soil type, and seasonal influences may be relevant. The AI extracts these connections from data and continuously learns.
4 4. Inline results integration A striking feature of AI Mode is that the answer is no longer separate from the rest of the page. You not only get an AI overview, but also direct links to sources, products (via Organic Shopping), FAQs, and follow-up questions. The AI experience is therefore not a replacement for search engine optimization, but an extra layer in which multiple content forms (such as videos, images, and structured data) work together. The more complete you are, the more often you can participate.
5 5. Assessment of reliability and source consistency In its technical documentation, Google also mentions that sources are weighted based on reliability, E-E-A-T, and consistency over time. This means that it’s not just about “what you write,” but also whether your content is consistent with what you communicate elsewhere (on your site or on other platforms). Branding, tone of voice, and author profiling are playing an increasingly important role in this.
6 6. Personalized AI results via user embeddings AI Mode personalizes responses not only based on the current session, but also on a broader, long-term user representation. Google uses so-called user embeddings for this purpose: vectors based on long-term signals such as previous searches, click behavior, content preferences, device interactions, and behavior in other Google services. This user embedding is injected into the AI model as latent ‘user language’ during four key phases: During query interpretation: how the intent of the question is understood. During fan-out generation: which related search queries are generated and taken into account. During passage retrieval: how sources are sorted based on personal relevance. During response construction: what form (list, paragraph, video) or tone the answer takes. This personalization takes place without the AI model needing to be retrained. A single generative model (such as Gemini) can thus serve billions of users in real time with unique answers. It also ensures consistency across platforms: what a user sees in AI Mode can match what they experience on YouTube, Gmail, or Google Shopping. For marketers, this represents a fundamental shift: relevance is no longer universal. Two people asking the same question may see different sources, formats, or answers. Purely based on who they are. This makes traditional rank tracking more limited for AI Mode. If you want to be truly visible, your content must perform across the full spectrum of user profiles. So think about how you add value for different personas and how your brand, content forms, and semantics resonate with diverse user contexts.
Optimize for entities and semantics Google is increasingly using entities and semantic relationships to organize information. Ensure your content aligns with existing concepts, utilizes structured data, and entity-focused keywords. Think beyond synonyms: AI understands meanings and relationships.
Build topical authority and depth With query fan-out, Google searches across a broad spectrum of related questions. If your site is consistently included in these searches, thanks to a broad and deep offering, you will be picked up more often. So don’t just build a single page on a topic, but a coherent ecosystem of supporting articles, guides, videos, and visuals.
Focus on featured snippets and AI mentions AI Mode reuses a lot of content that is already in featured snippets. Make sure you have clear headings, bullet points, and content that is short, factual, and contextually strong. Good snippet structures have an advantage in AI display.
Work on brand recognition and reliability AI must be able to trust sources. Brands that are well-known, communicate in a structured manner, and demonstrate consistency in content (e.g., through author profiles, reliable structure, and E-E-A-T signals) are more likely to be cited in AI responses.
Make content “AI-readable” and versatile Think in terms of elements: bullet points, tables, images with alt tags, and semantically clear structure. But also consider content such as videos, FAQs, and images that can be incorporated inline into AI interfaces. Optimize not only for SEO, but also for multimodal AI use.