Here’s the thing: the way AI search engines find and deliver information has fundamentally changed, and most content creators have no idea it’s happening.
When you type a query into Google’s AI Mode, ChatGPT, or Perplexity, you’re not just triggering a single search. You’re launching an entire fleet of searches. Behind the scenes, artificial intelligence is breaking your question apart, exploring multiple angles simultaneously, and synthesizing everything into one cohesive answer.
This process has a name. It’s called fan-out queries. And if you’re serious about optimizing content for AI, understanding how this works isn’t optional anymore, it’s essential for survival in modern search.
What Exactly Are Fan-Out Queries?
Let’s break it down simply.
A fan-out query is what happens when an AI search system takes your single question and expands it into multiple related sub-queries. Think of it like a detective who doesn’t just follow one lead, they chase down every possible angle at once, then piece together the full story.
Say you search for “best electric cars for families under $50,000.” A traditional search engine would scan for pages containing those exact words. But AI search? It fans out. It simultaneously searches for:
- “Family car safety ratings 2026”
- “Affordable electric SUVs”
- “Cargo space family vehicles”
- “Electric car range for road trips”
- “Best EV tax credits for families”
All of these queries run in parallel. The AI retrieves information from the live web, knowledge graphs, and specialized databases, then evaluates and combines these results using quality signals to create a single, coherent response.
This is the fundamental shift: AI search has moved from keyword matching to intent-based synthesis. It’s no longer about whether your page contains the right words. It’s about whether your content helps answer the constellation of questions surrounding a topic.
Why Fan-Out Queries Matter More Than You Think
Full disclosure: this changes everything about how we approach SEO and content strategy.
In the old world, you optimized a page for a keyword. You stuffed it with variations, built some links, and hoped Google’s algorithm liked you. Simple (if tedious).
In the AI search world, visibility depends on covering the full cluster of related topics and entities associated with your target keyword. Your content needs to anticipate the sub-queries that AI systems will generate, not just the question the user typed.
Here’s where it gets interesting: fan-out queries don’t just look for what users explicitly ask. They anticipate follow-up questions users might naturally ask next, incorporating relevant information even when not explicitly requested.
This means the AI is literally trying to read the user’s mind and keep them satisfied within a single search experience. If your content only answers the surface-level question, you’re invisible to the deeper retrieval process.
What Industry Experts Are Saying
This isn’t just theoretical. Some of the sharpest minds in SEO have been studying how AI search retrieval actually works, and their insights are gold for anyone trying to stay visible.
Marie Haynes on Gemini’s Query Expansion
Marie Haynes has been diving deep into how Google’s Gemini (what some call “Gemini 3”) processes and aggregates information. Her research highlights how AI doesn’t just pull from one source, it actively synthesizes data from multiple queries to build comprehensive answers.
The implication? Your content needs to be the kind of authoritative, well-structured resource that AI wants to pull from when it’s building those synthesized responses. Thin content that only scratches the surface won’t cut it.
Duane Forrester’s Question Maps
Duane Forrester’s work on his Substack has introduced a concept that maps perfectly to fan-out queries: Question Maps.
The idea is that every topic has a web of related questions surrounding it, questions users might ask before, during, and after their primary search. Forrester argues that these question maps are essentially what AI systems use for retrieval. When you map out the full landscape of questions around your topic and create content that addresses them, you’re building exactly what AI systems are looking for when they fan out.
This is why tools like content gap analysis have become so critical. You need to identify not just what you’re ranking for, but what related questions you’re missing entirely.
Michael King on AI Mode Manipulation
Michael King has been characteristically blunt about how AI Mode manipulates content and why SEOs must adapt. His perspective emphasizes that AI systems aren’t just retrieving content, they’re transforming it, summarizing it, and often presenting it without traditional click-through.
King’s point is that SEOs need to stop thinking about rankings alone and start thinking about citation. The question isn’t “Will I rank?” It’s “Will my content be selected as a source when AI constructs its answer?”
This requires a different optimization mindset. Your content needs clear, quotable statements. Definitive answers. Well-organized information that AI can easily extract and attribute.
Cyrus Shepard on User Intent and Relevance
Cyrus Shepard’s work has always emphasized user intent and high-relevance content, and it’s never been more applicable than now. In a fan-out query world, intent isn’t just about what the user typed, it’s about the entire spectrum of needs surrounding that search.
Shepard’s focus on creating content that deeply satisfies user intent aligns perfectly with what AI systems reward. They’re not looking for pages that technically match a query. They’re looking for resources that comprehensively serve the user’s underlying goal.
How Fan-Out Queries Transform Your Content Strategy
Okay, enough theory. Let’s talk about what you should actually do with this information.
Build True Topic Clusters
If fan-out queries mean AI is searching for related sub-topics simultaneously, then your content architecture needs to reflect that. Building genuine topic clusters: where a pillar page links to comprehensive supporting content covering every angle: positions you to be retrieved across multiple fan-out sub-queries.
This isn’t just internal linking for SEO’s sake. It’s about creating a content ecosystem that mirrors how AI systems explore topics.
Expand Your FAQ Coverage
Fan-out queries anticipate follow-up questions. You should too.
Every piece of content you publish should consider: What would someone naturally ask next? What related questions sit adjacent to this topic? Build out FAQ sections that address these secondary and tertiary questions. Use tools like our AI Content Auditor to identify where your content might be missing the depth AI systems crave.
Optimize for Citation, Not Just Clicks
Here’s the uncomfortable truth: in a world of AI-synthesized answers, you might get cited without getting clicked. This is the “zero-click” reality we’ve discussed before.
But citation still matters. It builds brand awareness, establishes authority, and: when AI systems attribute sources: it can drive qualified traffic from users who want to go deeper.
To get cited, your content needs:
- Clear, definitive statements that AI can extract
- Well-organized structure with logical headings
- Original insights that differentiate you from commodity content
- Proper entity and topic coverage that demonstrates comprehensive expertise
Use the Right Tools
Adapting to fan-out queries requires understanding where your content gaps are and how your existing content performs against AI retrieval standards. Our optimization and analysis tools are designed specifically for this new landscape: helping you identify opportunities and weaknesses in your content ecosystem.
The Bottom Line: Adapt or Disappear
Fan-out queries aren’t a future prediction. They’re happening right now, every time someone uses AI-powered search. Google’s AI Mode, ChatGPT, Perplexity, and every other AI search tool is breaking user queries into sub-queries, retrieving information from multiple angles, and synthesizing comprehensive answers.
Your content either participates in that process: or it doesn’t exist.
The businesses that will thrive in AI search are those that understand this fundamental shift: it’s no longer about matching keywords. It’s about comprehensively serving intent across the full spectrum of related questions.
That requires smarter content strategy, better topic architecture, and a willingness to create depth instead of just volume.
Ready to optimize your content for AI search? Book a consultation with Expert SEO Consulting and let’s map out how fan-out queries apply to your specific business and content strategy.
