New Google Insights on the Query Fan-Out Technique in AI Mode

Google’s AI Mode isn’t just answering your questions — it’s generating its own search queries behind the scenes to find the best possible answer. This process, known as query fan-out, is one of the most significant shifts in how Google Search operates in the AI era. And thanks to new details shared by Google’s VP of Product for Search, Robby Stein, we now have a much clearer picture of how this technology actually works — and what it means for SEO.

What Is the Query Fan-Out Technique?

When a user types a question into Google’s AI Mode, the system uses a large language model to interpret that query and then “fan out” multiple related searches — many of which may cover topics the user never explicitly mentioned.

Think of it as Google putting on a research hat. Instead of simply matching your words to indexed pages, AI Mode acts more like a curious assistant — anticipating what you really need, breaking it down into sub-questions, and running all of them simultaneously in the background.

Robby Stein illustrated this with a practical example: if someone asks about things to do in Nashville with a group, the system might independently search for great restaurants, bars, and kid-friendly activities — all without the user specifying any of those. He described the system as using Google Search as a backend tool, executing multiple queries and combining the results into a single response with links.

This isn’t just a feature of AI Mode. The functionality is active across AI Mode, Deep Search, and some AI Overview experiences.

The Scale Behind It

The numbers here are staggering. Stein noted that AI-powered search experiences, including query fan-out, now serve approximately 1.5 billion users each month — spanning both text-based and multimodal input.

The data powering these responses goes well beyond traditional web crawls. Underlying data sources include traditional web results as well as real-time systems like Google’s Shopping Graph, which updates 2 billion times per hour.

Stein referred to Google Search as “the largest AI product in the world” — and with that kind of infrastructure behind it, query fan-out isn’t a novelty feature. It’s quickly becoming the default mode of search.

How Deep Search Takes It Further?

For complex queries, Google can escalate the process through a mode called Deep Search. In cases where Google’s systems determine a query requires deeper reasoning, Deep Search may be triggered — issuing dozens or even hundreds of background queries, sometimes taking several minutes to complete.

Stein shared a personal example: he used Deep Search to research home safes before making a purchase — a topic involving unfamiliar technical factors like fire resistance ratings and insurance implications. The system spent several minutes gathering information and returned a comprehensive response covering how ratings work, specific safe recommendations, and links to reviews for further reading.

This kind of depth represents a fundamental change in what “search” means. Google is no longer just pointing you to relevant pages — it’s doing preliminary research on your behalf and synthesising it for you.

Access to Google’s Internal Tools

One of the more revealing parts of Stein’s interview was how deeply integrated AI Mode is with Google’s own data ecosystems.

Stein mentioned that AI Mode has access to internal Google tools, including Google Finance and other structured data systems. For example, a stock comparison query might involve identifying relevant companies, pulling current market data, and generating a chart.

Similar processes apply to shopping, restaurant recommendations, and other query types that rely on real-time information. He highlighted that integrated systems now include flight data, movie information, and a shopping catalogue of 50 billion products — updated approximately 2 billion times every hour.

This means Google’s AI isn’t just pulling from the open web — it has first-party data pipelines that are continuously refreshed, giving its responses a level of real-time accuracy that external sources simply can’t match.

The Connection to Google’s “Thematic Search” Patent

Stein’s description of query fan-out closely mirrors a Google patent filed in December around a concept called “thematic search.”

That patent outlines a system that creates sub-queries based on inferred themes, groups results by topic, and generates summaries using a language model — with each theme capable of linking back to source pages, while summaries are compiled from multiple documents.

This approach differs from traditional search ranking by organising content around inferred topics rather than specific keywords. While the patent doesn’t confirm implementation, it closely matches Stein’s description of how AI Mode functions.

For SEOs, this is a critical distinction. Google isn’t just ranking pages for keyword matches anymore — it’s grouping content thematically and assigning it relevance within a broader contextual cluster.

What This Means for SEO Strategy?

The query fan-out technique has profound implications for how digital marketers and SEO professionals should think about content and visibility.

1. Keyword targeting alone is no longer sufficient

When Google autonomously generates its own sub-queries, the concept of “targeting a keyword” becomes more nuanced. Your content may surface not because it matches a user’s exact search, but because it fits a theme that Google’s LLM infers is relevant to the user’s broader intent.

2. Topical authority matters more than ever

If Google is fanning out into related topic clusters around a core query, sites that demonstrate deep, comprehensive coverage of a subject are more likely to be pulled into those background searches. Building topical authority — covering a subject from multiple angles — is no longer just good practice; it’s essential for AI Mode visibility.

3. Structured, source-friendly content is a must

Because AI Mode compiles answers from multiple documents and links back to sources, your content needs to be clearly structured, factually accurate, and easy to parse. Schema markup, clear headings, and well-organised FAQs all help signal the relevance of your content within a thematic cluster.

4. Real-time data and freshness signals matter

Given that Google’s AI is drawing from systems updated billions of times per hour, stale content is a liability. Regularly updated pages, current statistics, and timely commentary on industry developments will be better positioned for inclusion in AI-generated responses.

5. Attribution and measurement will get harder

With Google explaining how AI Mode generates its own searches, the traditional boundaries of what counts as a “query” are beginning to blur — creating challenges not just for optimisation, but for attribution and measurement. Traffic may arrive via paths that don’t neatly correspond to the keywords you’ve been tracking.

The Bigger Picture

Query fan-out represents a maturation of how search engines understand intent. Rather than treating each search as an isolated transaction, Google is now modelling the research process a human would go through — and then doing much of that process autonomously.

As search behaviour becomes more fragmented and AI-driven, marketers may need to focus less on ranking for individual terms and more on being included in the broader context that AI pulls from.

This is a shift from visibility at the keyword level to visibility at the topic and context level — and it requires a rethink of content strategy, internal linking, topical clustering, and how we measure success in organic search.

Conclusion

Google’s query fan-out technique isn’t a future development — it’s already powering responses for 1.5 billion users every month. The details Robby Stein shared give us a rare look into the mechanics of AI Mode and confirm what many SEOs have been suspecting: the game has changed.

The brands and content creators who adapt — by thinking in topics rather than keywords, by building structured and authoritative content ecosystems, and by staying current — will be best positioned to earn visibility in this new era of AI-driven search.