Query fan-out is a technique used in AI search in which the system breaks one question into several related sub-queries and runs them at the same time. The results of all sub-queries are then combined into a single answer. Google says it uses the technique in AI Mode and AI Overviews.
At a glance
- Type
- technique used in AI search
- Used in
- Google AI Mode and AI Overviews (according to Google)
- Visible?
- Google does not show the sub-queries, not even in Search Console
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How does query fan-out work?
Google’s guide to generative AI features defines query fan-out as a set of concurrent, related queries that the model generates to fetch additional relevant search results for the user’s question. The AI Mode help page describes it as dividing the question into subtopics and searching for each one simultaneously. The searches can run across the web and Google’s own data sources, such as the Knowledge Graph and shopping data.
Google described the technique when it introduced AI Mode on March 5, 2025. At Google I/O on May 20, 2025 it presented Deep Search, which applies the same approach on a larger scale and, according to Google, can issue hundreds of searches to produce a fully cited report.
The word itself comes from computing, where “fan-out” means sending one request to many targets at once, for example to several database shards. In SEO discussions it almost always refers to the AI search meaning.
What does query fan-out mean for SEO?
A page can be cited in an AI answer without ranking for the original question, because it answers one of the sub-queries well (an inference from the method, not a Google statement). Google does not show which sub-queries a system generated. Neither the Performance report nor the Generative AI performance report in Search Console lists them; the latter shows impressions per page, country and device only. SEO tools try to reconstruct likely sub-queries with their own models. Their output is an estimate.
In practice this means sub-questions of a topic benefit from clear, findable answers, for example in a section with a descriptive heading. The entry requirement stays the same as in classic search. Google’s AI features only link to pages that are indexed and eligible to show with a snippet.
Example
A user asks AI Mode: “Is a heat pump worth it in a house built in 1960?” The system might derive sub-queries such as:
- heat pump older house efficiency flow temperature
- heat pump installation cost older home
- heat pump rebates 2026
- replacing radiators for a heat pump
The answer summarizes the findings and links pages that cover individual sub-questions. This list is a simplified illustration. The real sub-queries are not published.
FAQ
What does “query fan-out” mean? Spreading one search request out into several narrower searches whose results are merged. Google uses the term for how AI Mode and AI Overviews research a question.
How can I find fan-out queries? Not directly. Google does not expose them. Approximations come from People Also Ask boxes, related searches, prompt experiments and tools that simulate sub-queries.
Does query fan-out only exist at Google? Google is the provider that documents it by name. Other AI search systems can also run several searches per question, but the public documentation reviewed here does not describe the method.
Sources
- AI features and your website – Google Search Centraldevelopers.google.com
- Google's guide to optimizing for generative AI features on Google Search – Google Search Central (updated 2026-07-10)developers.google.com
- Expanding AI Overviews and introducing AI Mode – Google Blog, 2025-03-05blog.google
- AI in Search: Going beyond information to intelligence – Google Blog, 2025-05-20blog.google
- Get AI-powered responses with AI Mode in Google Search – Google Search Helpsupport.google.com
- Generative AI performance report – Search Console Helpsupport.google.com
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