Introduction
Search is changing fast. When someone types a question into Google, they usually trigger a single keyword-based query. But when that same question is asked in ChatGPT or Gemini, something very different happens behind the scenes.
Modern AI search doesn’t rely on one query. Instead, large language models break a single prompt into multiple background searches to fully understand intent, context, and relevance. This process is called query fan-out, and it’s becoming one of the most important — and least understood — shifts in search visibility.
In this article, we’ll explain what query fan-out is, show a real example captured by getaiso.com, and break down why brands that rank well on Google may still be invisible in AI-generated answers.
What Is Query Fan-Out?
Query fan-out is the process by which AI models like ChatGPT and Gemini expand a single user prompt into multiple related search queries.
- • One user prompt → multiple background searches
- • Each search targets a different intent, attribute, or subtopic
- • The final AI response is synthesized from all of them
A Real Example: From One Prompt to Many Searches
Let’s look at a real prompt captured using getaiso.com’s Conversations Intelligence tool.
A user asked:
“What are the best resorts for families in the Bahamas when traveling over the 4th of July?”
From the user’s perspective, this looks like a single, straightforward question. But ChatGPT doesn’t answer it with just one search.
Instead, it decomposes the prompt into multiple intent-driven searches to understand:
- The destination (Bahamas)
- The audience (families)
- The timing (4th of July)
- The decision factors (amenities, kid-friendliness, beaches)
Behind the Scenes: Real Fan-Out Queries
Using the getaiso.com Fan-Out feature, we can see the actual background queries triggered by this prompt.
Query A
“best Bahamas family resorts amenities kids pools beaches Bahamas resorts family friendly”Focuses on amenities and features important to families (kids, pools, beaches).
Query B
“family friendly resorts Bahamas”Captures broad family-friendly positioning within the destination.
The AI gathers results across these queries, evaluates them, and then generates a single, polished answer for the user.
Why Query Fan-Out Changes SEO Visibility
This is where things get interesting — and risky — for companies. Most SEO strategies are built around ranking for a defined set of Google keywords. You optimize pages, track rankings, and measure traffic based on those terms.
But AI search doesn’t care if you rank for just one keyword.
If your brand ranks well for your usual Google search keywords but does not rank for the fan-out queries AI is using, then you may not appear at all in ChatGPT or Gemini responses.
The Fan-Out Awareness Gap
Many companies don’t realize this gap exists. They may dominate a narrow keyword like “Bahamas family resort” while missing broader or more specific fan-out queries. If you only rank for a subset, your brand may never make it into the AI’s consideration set.
How getaiso.com Makes Fan-Out Visible
This is exactly the problem getaiso.com is built to solve. With the Fan-Out feature, companies can:
- ✓See the fan-out queries generated for any prompt
- ✓View latest Google results for each fan-out keyword
- ✓Identify which brands AI is likely drawing from
- ✓Spot gaps where they don't rank — but should
See the Fan-Out Feature in Action
🎯Closing Thoughts
Query fan-out is not a future trend — it’s how AI search works today. If your brand wants to stay visible as users move from Google to ChatGPT and Gemini, understanding and optimizing for fan-out queries is no longer optional.