Fan-out queries is a term used to describe the behaviour of AI search systems that decompose a single complex user question into multiple sub-queries, execute each one independently against a search index or knowledge base, and then synthesise the retrieved results into a unified answer. Google described a form of this architecture in patents and developer documentation related to the Search Generative Experience, noting that a query such as “best running shoes for flat feet under £100” might fan out into separate retrievals for shoe recommendations, flat-foot biomechanics, and current pricing data. For SEO practitioners, fan-out behaviour means that a single page is unlikely to satisfy every sub-query in isolation; instead, topically comprehensive content that covers related facets of a subject tends to be retrieved more often across the fan of sub-queries. Understanding fan-out patterns can inform content architecture decisions and internal linking strategies.