Byline: Gregg Kell | Editor, SpotlightOnStartups.com
What is Query Fan-Out?
Have you ever asked ChatGPT a question about your own industry, and your company never showed up? You are not alone. A growing number of business buyers now ask AI tools for recommendations before they ever type a word into Google. In one widely cited 2024 survey, half of B2B software buyers said they now start their research in an AI chatbot instead of Google Search. That number jumped 71 percent in just four months. A follow up study found that almost eight out of ten business buyers say AI search has already changed how they research companies.
So if a buyer asks an AI assistant a question about your industry, and your company is not in the answer, you have a real problem. To understand why this happens, you need to understand one idea: query fan-out.
What Is Query Fan-Out?
Query fan-out is the way AI search tools turn one simple question into many smaller questions, all at once, before they ever write an answer.
Here is an example. Say someone types “best project management tools for remote teams” into an AI search tool. The AI does not just look up that exact sentence. Instead, it quietly runs several related searches in the background, such as “top project management software,” “remote team collaboration features,” and “project management pricing comparison.” Then it blends everything it finds into one smooth answer.
Google was the first company to use the term “query fan-out” in public, when it introduced AI Mode and built a custom model specifically for breaking questions apart. Since then, the idea has spread to nearly every AI search tool, including ChatGPT, Perplexity, and Google’s regular AI Overviews. Google’s own official documentation on this topic confirms that its AI features rely on this exact technique to surface content.
The simple version: one question goes in. Many hidden questions come out. Whichever company answers the most of those hidden questions clearly wins the spot in the final answer. Our own Entity Anchor explainer covers a related piece of this puzzle, how AI tools confirm a company is a real, trustworthy entity before it ever gets cited.
How Is Query Fan-Out Different From Old Fashioned Keyword Search?
Old search worked like this: you typed a phrase, and the search engine tried to match that exact phrase to web pages. Ranking number one for that one phrase was the whole goal.
Query fan-out changes the game completely. Instead of matching one phrase, the AI is comparing your content against a whole map of related questions at the same time. Your page is no longer just competing for one search. It is competing across an entire cluster of hidden searches that most business owners never even see, a shift that Ahrefs has documented in detail as it rewrites the rules SEOs spent decades optimizing around.
This is why a company can rank well on Google and still be completely missing from an AI generated answer. Ranking for one keyword is no longer enough. Our guide to optimizing content for AI search walks through what replaces single keyword targeting once fan-out enters the picture.
Is Query Fan-Out the Same Thing as RAG?
Not quite, but the two ideas are closely related, and people mix them up all the time.
RAG stands for Retrieval Augmented Generation. It is the overall process AI tools use to look up fresh information on the web before answering a question, instead of only relying on what they learned during training.
Query fan-out is one specific technique inside that process. Picture it this way: RAG is the whole research trip. Query fan-out is the part where the AI sends out several researchers at once, each one chasing a slightly different angle of the same question, then brings all their notes back together into one final answer. Semrush breaks down this exact relationship in its own technical guide, for anyone who wants to go deeper on the mechanics.
How Do ChatGPT, Perplexity, and Google Each Handle Fan-Out Differently?
This is the part most business owners miss completely. AI search tools are not all the same. Each one fans out questions a little differently, and each one prefers different kinds of sources when it builds its final answer, a pattern iPullRank has mapped out across the major platforms.
| AI Tool | How It Fans Out Questions | What It Tends to Trust |
|---|---|---|
| Google AI Mode | Built on a custom AI model made specifically for breaking questions apart. Simple questions get several sub questions. Complex questions can trigger hundreds of background searches. | Leans on Google’s existing search rankings as a starting point |
| ChatGPT | Runs ten or more background searches for a complex question, often searching specific company websites directly. | Strongly favors encyclopedia style sources and other well known reference sites |
| Perplexity | Searches the open web for almost every question it receives, not just complex ones. | Leans heavily on online community discussions, far more than the other tools |
One especially interesting fact: research from Discovered Labs comparing how each platform cites sources found that only about one in ten companies that get mentioned by ChatGPT are also mentioned by Perplexity for the exact same question. That means showing up in one AI tool does not guarantee you will show up in another. Each one needs its own strategy. Our guide to AI search visibility audits explains how to check your own visibility across each platform separately.
Why Does This Matter Even More for B2B Startups?
If you sell to other businesses, this trend is moving fast, and most founders have not caught up yet. A 2026 B2B SaaS citation benchmark study found that a growing share of business buyers, climbing toward three out of four, now use AI tools somewhere in their research process before they ever contact a vendor.
Researchers have also found something practical and useful here. An analysis of more than 170,000 cited web pages found that pages including specific numbers, named sources, and clear methodology notes saw their visibility across AI tools improve by more than 20 percent compared to pages full of vague claims. In plain words, facts beat feelings when it comes to getting noticed by AI. This is exactly why our Best Orange County AEO Services guide stresses entity clarity and verifiable claims over vague marketing language.
Why Isn’t My Startup Showing Up When Someone Asks AI for a Recommendation?
Here is the part that stings a little. AI tools like ChatGPT do not work like an old fashioned search engine. They do not hand someone a list of ten links and let the person pick one. Instead, the AI quietly chooses a small handful of companies it feels confident recommending by name, and says them out loud in its answer.
If your company is not inside that small handful, it simply does not exist at the moment a buyer is deciding who to call. One detailed breakdown of why businesses go missing from ChatGPT puts it plainly: the model needs confidence that a source is accurate and unambiguous, and it cannot get that confidence from a brand’s own website alone.
This usually has nothing to do with how good your product actually is. It almost always comes down to one thing: the AI does not have enough clear, trusted, outside information about your company to feel confident naming you. If the only place your story is told is on your own website, the AI has no way to confirm any of it is true. It needs to see your story confirmed somewhere else, written by somebody other than you.
So What Actually Helps a Startup Win More of These Hidden Questions?
This is exactly the gap that a real, independent news story fills, and it is also exactly the gap that most AEO advice completely skips over.
A journalist authored feature article, published on an independent media site, works differently than a page on your own company website. It gives outside, third party proof that real human beings, not just your own marketing team, recognize your company and can describe what it does in clear, specific language. That is the exact kind of outside confirmation an AI search tool is looking for before it will confidently say your name out loud.
This is also the entire reason SpotlightOnStartups.com exists. We are the only AEO media platform built to be the earned media citation itself, not just another technical fix bolted onto a website. A published, journalist written founder spotlight gives an AI search tool exactly the kind of independent, fact filled source it is hunting for when it fans a question out into dozens of smaller questions behind the scenes.
If you want to see how this looks once it is actually published, our Founder’s Complete Guide to Getting Cited by AI walks through the citation stage in detail, and our 2026 Startup Guide to Ranking in AI Search breaks down the retrieval and ranking steps that come before it. You can see what an outside, independently reported AEO story actually looks like in our recent GrackerAI founder feature on the AI search war in cybersecurity.
Ready to get your own company’s story published as the kind of independent, fact filled source AI search tools are already hunting for? Get featured on SpotlightOnStartups.com and start building the outside proof your next AI mention is missing.
Frequently Asked Questions
What does “query fan-out” actually mean, in simple terms? It means an AI search tool takes one question a person asks and quietly turns it into several smaller, related questions, runs them all at once, and then blends the answers into one response.
Who created the term “query fan-out”? Google was the first company to use the term publicly, when it launched its AI Mode search feature. Other companies, including OpenAI and Perplexity, use the same basic idea even though they do not all use the exact same name for it.
Is query fan-out the same thing as RAG? No. RAG, or Retrieval Augmented Generation, is the bigger process of an AI tool looking up fresh information before answering. Query fan-out is one specific technique used inside that process, the part where one question becomes many.
Does every AI search tool use query fan-out the same way? No. Google, ChatGPT, and Perplexity each fan-out questions differently and trust different kinds of sources, which is why a company can show up clearly in one AI tool and be completely missing from another.
Why would a well ranked website still get skipped by an AI search tool? Because ranking high in regular search results is no longer the only test. The AI is checking your content against an entire cluster of hidden related questions, and it is also looking for outside proof of your story, not just your own claims about yourself.
Can a small or new startup actually compete here against bigger, older companies? Yes. Since the AI is hunting for clear, specific answers to narrow questions rather than rewarding the oldest or biggest website, a smaller company with a clear, well documented story can win a specific question even against a much larger competitor.
What is the single most useful first step for a startup founder who feels invisible to AI search tools right now? Get your company’s story published by an independent source that AI tools already trust, with clear facts, named people, and specific details. A self written page on your own site cannot do this alone, since the AI cannot use it to confirm your story is true.