What You'll Learn
- What query fan-out is and how AI search engines use it to answer questions
- Why pages with comprehensive topic coverage get 161% more AI citations than single-keyword pages
- Why traditional keyword optimization is no longer enough for AI visibility
- Practical steps to make your content show up in AI-generated responses
- How to structure your website content for comprehensive topic coverage
If you’ve noticed your website traffic patterns changing, you’re not alone. AI search engines like ChatGPT, Google’s AI Mode, and Perplexity are changing how people find information online. Behind these changes is a technique called query fan-out, and it’s reshaping what it means to optimize your content for search.
Understanding query fan-out isn’t just for tech companies. If you run a law firm, accounting practice, manufacturing business, or commercial construction company, this shift affects how potential clients discover your services.
Recent data confirms this shift. An analysis of 10,000 keywords found that pages ranking for multiple related queries are 161% more likely to be cited in AI responses than pages optimizing for a single keyword. The old playbook doesn’t work anymore.
What Is Query Fan-Out?
Query fan-out is how AI search systems break down a single question into multiple smaller questions to gather better information. Instead of just searching for your exact words, AI engines analyze what you really want to know and search for several related things at once.
Think of it this way: when someone asks an AI, “What’s the best project management software for remote teams?” the AI doesn’t just look for pages with those exact words. It breaks that question into pieces:
- Reviews of project management tools
- Software designed for remote work
- Comparison articles between popular platforms
- User experiences with different tools
- Pricing and features for team collaboration software
The AI searches for all these angles at once, then combines the best information into a single, comprehensive answer.
Google officially explained this process during their I/O conference in May 2025. Elizabeth Reid, Google’s Head of Search, described it as letting AI “break the question into different subtopics and issue a multitude of queries simultaneously on your behalf.”
Why This Matters for Your Business
Traditional search worked pretty simply. Someone typed in keywords, and Google showed pages that matched those keywords best. If you optimized your website for the right keywords, you had a good chance of showing up.
AI search works differently. These systems don’t just match keywords. They try to understand the full context of what someone needs, even if that person didn’t know how to ask for it. When AI generates an answer, it might pull information from several sources, synthesize that information, and present it without anyone clicking through to your website.
This means your potential clients might learn about solutions to their problems, compare options, and make decisions without ever visiting your site. Unless your content appears in those AI-generated responses, you’re invisible in this new search environment.
According to research from Semrush, websites that appear in AI responses see better brand visibility and increased authority in their industries. The companies that adapt early will have a significant advantage over competitors still focused only on traditional SEO.
What the Data Shows About AI Citations
Recent analysis of 10,000 keywords by Surfer SEO revealed something that changes how we think about AI optimization. Pages ranking for fan-out queries are 161% more likely to be cited in Google AI Overviews than pages ranking only for the main search term.
Here’s what the numbers show:
- 76% of keywords now trigger AI Overviews
- Pages ranking for both the main query and related fan-outs account for 51% of all AI citations
- Pages ranking only for the main query? Under 20% of citations
- About 30% of citations go to pages that rank only for fan-out queries (not the main term at all)
Even more interesting: 68% of pages cited in AI Overviews don’t rank in the top 10 for the main query or any fan-out query in traditional search results.
This means AI engines aren’t just rewarding traditional SEO rankings. They’re looking for comprehensive topical coverage and authoritative information, regardless of where you rank.
The catch: Fan-outs are dynamic and context-dependent. Only about 27% of fan-outs remain consistent across different users and contexts. You can’t predict them all, and you can’t optimize for them individually.
Instead, the winning strategy is simple: own the topic. Build such thorough coverage of your subject area that you naturally capture fan-out queries you never explicitly targeted.
How AI Fan-Out Changes Content Strategy
The shift from keyword optimization to query fan-out requires rethinking your entire content approach. Here’s what changes:
From Keywords to Topics
Traditional SEO focused on ranking for individual keywords. AI optimization requires covering entire topics comprehensively. If you’re a law firm specializing in maritime law, you can’t just optimize a page for “maritime injury lawyer.” You need content that addresses:
- Types of maritime injuries
- Jones Act claims process
- Offshore worker rights
- Longshore and Harbor Workers’ Compensation Act
- Case timelines and expectations
- Settlements versus trials in maritime cases
- State versus federal jurisdiction
Each of these topics represents a potential fan-out query. AI engines look for depth and breadth. They want to find sites that demonstrate real expertise across a subject area, not just a single optimized page.
Here’s proof this approach works: in a study of 10,000 keywords, pages with comprehensive coverage across multiple related queries accounted for 51% of AI citations. Pages focused only on ranking for a single keyword captured less than 20%. Even more telling, about 30% of AI citations went to pages that ranked only for related subtopics, not the main term at all. Your comprehensive coverage creates multiple entry points for AI systems to discover your expertise.
Anticipating Follow-Up Questions
AI search is conversational. When someone asks a question, the AI thinks about what they might ask next and includes that information proactively. Your content should do the same thing.
For example, if you write about sales tax compliance software, don’t just explain what it is. Anticipate the natural follow-up questions:
- How much does it cost?
- How long does implementation take?
- What integrations are available?
- Who is it best suited for?
- What problems does it solve?
When your content naturally flows from one question to the next, AI engines recognize it as more helpful and complete.
Creating Content Clusters
Content clusters organize your website around core topics with supporting pages for subtopics. This structure helps AI engines understand your expertise and find relevant information quickly.
A good cluster includes:
A pillar page that provides a broad overview of the main topic Cluster pages that dive deep into specific aspects Internal links connecting related content
For a construction management firm, a pillar page might cover “Construction Project Management Best Practices.” Cluster pages would then address specific areas like scheduling, budget control, subcontractor management, safety compliance, and change order processes.
This organization signals topical authority. AI engines can find comprehensive information on your site and recognize you as a legitimate expert in your field.
Old SEO vs. New AI Optimization: A Real Example
Old approach (keyword-focused): A law firm creates a page optimized for “maritime injury lawyer” with that exact phrase used strategically throughout. They rank #3 for that term.
Result: Gets few AI citations because coverage is too narrow.
New approach (topic-focused): The same law firm creates:
- Pillar page on maritime law and injury claims
- Detailed pages on Jones Act claims, offshore worker rights, LHWCA coverage
- FAQ pages addressing common questions about maritime jurisdiction, settlement timelines, and case processes
- Case studies showing specific outcomes
- Blog posts about recent maritime law developments
Result: Gets cited in AI responses for dozens of related queries they never explicitly targeted. Shows up when people ask about “offshore injury compensation,” “Jones Act eligibility,” “maritime vs. workers’ comp,” and many other variations. Total visibility increases dramatically even though they may not rank #1 for any single term.
The second approach creates multiple surfaces for AI discovery. Data shows this captures 161% more citations than single-keyword optimization.
Practical Steps to Optimize for Query Fan-Out
Audit Your Current Content
Review your existing content to identify gaps. Look at your main service pages and ask:
- What questions might someone have about this service?
- What problems are we solving?
- What concerns might someone have before hiring us?
- What would someone need to know to make an informed decision?
Make a list of every question you can think of. These are potential fan-out queries that AI engines might generate.
Write in Clear Sections
Structure your content with descriptive headings that clearly state what each section covers. AI engines parse content by sections, pulling specific information to answer specific queries.
Instead of creative headings like "What We Bring to the Table," use direct headings like "Our Process for Sales Tax Compliance." Be literal. Make it obvious what information each section contains.
Use short paragraphs, bullet points, and numbered lists when appropriate. AI engines can extract and present this information more easily when it's well organized.
Answer Questions Completely
When you address a topic, cover it thoroughly in that section. Don't assume someone read the paragraph above or will continue to the next section. AI engines often extract individual chunks of content, so each section should stand on its own.
Include relevant context. Define terms when you introduce them. If you mention a specific law or regulation, briefly explain what it is before diving into details.
Implement Schema Markup
Schema markup adds labels to your content that help AI engines understand what they’re looking at. This structured data makes it easier for AI systems to extract specific information like:
- Service descriptions
- Pricing
- Location
- Business hours
- FAQs
- Reviews and ratings
For professional services, FAQ schema is particularly valuable. It explicitly tells AI engines, “Here’s a question and here’s the answer,” making it easy to pull that information into responses.
Focus on Your Expertise
AI engines prioritize authoritative, trustworthy sources. Google calls this E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). Show your credentials:
- Include author bios with relevant qualifications
- Reference specific case studies or projects
- Cite data from your own experience
- Demonstrate deep knowledge of your field
- Get mentioned by other authoritative sites in your industry
Don’t just say you’re an expert. Prove it through the depth and quality of your content.
Create Original, Valuable Content
AI engines can summarize information that already exists online. What they can’t replicate is unique insight from your experience. Original research, proprietary data, specific case examples, and practical lessons learned are all valuable because they’re not available anywhere else.
This could be:
- A white paper analyzing trends you’ve observed in your industry
- Case studies showing specific results you achieved for clients
- Original research from surveys or data analysis
- Detailed how-to guides based on your methodology
- Lessons learned from real projects
This type of content gives AI engines something unique to cite and positions you as a thought leader rather than just another service provider.
Stop Chasing Individual Fan-Out Queries
This might seem counterintuitive after everything we’ve discussed about fan-outs, but here’s an important clarification: you cannot and should not try to identify and optimize for specific fan-out queries.
Why? Fan-outs change based on user context, search history, location, and other personalization factors. Only about 27% of fan-outs remain consistent across different searches. The rest are dynamic and unpredictable.
Instead of chasing individual fan-outs, focus on building comprehensive topical authority. When you thoroughly cover a subject from multiple angles, you naturally rank for numerous related queries you never explicitly targeted. This is how pages that don’t rank in the top 10 for anything still get cited in AI responses.
Think of it like casting a wide net versus trying to catch specific fish. Comprehensive coverage is your net. It captures relevance across hundreds of potential variations you can’t predict.
Common Mistakes to Avoid
As businesses adapt to query fan-out, watch out for these pitfalls:
Over-optimizing for AI at the expense of humans. Your content still needs to engage actual people. If someone does visit your website, the content should be compelling and readable, not just technically optimized.
Treating AI optimization as separate from traditional SEO. Many best practices overlap. Good AI optimization is also good traditional SEO. Comprehensive content, clear structure, and authoritative information help with both.
Ignoring the basics. Schema markup and content clusters won’t help if your site loads slowly, doesn’t work on mobile, or has major technical issues. Keep your technical foundation solid.
Creating shallow content at scale. Comprehensive doesn’t mean long and repetitive. It means thorough. Quality beats quantity. Five excellent, detailed pages beat fifty superficial ones.
Trying to identify and optimize for specific fan-out queries. The data shows that fan-outs are highly dynamic, with only 27% remaining consistent across users. You can’t predict them all, so don’t try. Focus on comprehensive topic ownership instead. This creates natural coverage that captures fan-outs automatically.
Unlike traditional SEO where you could track specific keyword rankings, AI visibility requires different metrics:
- Brand mentions in AI responses: Are AI engines mentioning your business when answering relevant questions?
- Citation coverage across fan-outs: Are you being cited for the main topic and related subtopics?
- Share of voice in your industry: How often are you mentioned compared to competitors?
- Topic coverage breadth: How comprehensively does your site cover your core service areas?
- Citation quality: Are you cited in top 3 visible positions in AI responses?
Remember that 68% of pages cited in AI Overviews don’t rank in the top 10 for traditional search queries. This means traditional ranking metrics alone won’t tell the full story of your AI visibility.
Tools like Semrush’s AI Visibility Toolkit can help track these metrics, showing where your brand appears across different AI platforms.
The Bottom Line
Query fan-out represents a fundamental shift in how search engines work. Instead of matching keywords, AI systems now understand topics, anticipate needs, and synthesize information from multiple sources.
For B2B businesses and professional service firms, this means your content strategy must evolve. Focus on comprehensive topic coverage, anticipate follow-up questions, organize content clearly, and demonstrate real expertise.
The data proves this approach works. Pages with comprehensive topical coverage get 161% more AI citations than single-keyword pages. The businesses that adapt to these changes early will have a significant competitive advantage.
Your potential clients are already using AI to research solutions and find service providers. The question is whether they’ll find you.
Start by auditing your current content, identifying gaps, and building out comprehensive coverage of your core topics. The investment you make now in creating authoritative, well-structured content will pay dividends as AI search continues to grow.
Sources and Further Reading
This article draws on research and analysis from leading voices in AI search optimization:
- Goodwin, Danny. “AI Overview fan-out rankings boost citation odds by 161%: Study.” Search Engine Land, December 18, 2025. https://searchengineland.com/ai-overview-fan-out-rankings-boost-citation-odds-study-466426
- Handley, Rachel. “What Is Query Fan-Out & Why Does It Matter?” Semrush Blog, August 12, 2025. https://www.semrush.com/blog/query-fan-out/
- Alla, Praneeth. “Introducing Query Fanouts: See what Answer Engines are really searching for.” Profound Blog, October 8, 2025. https://www.tryprofound.com/blog/introducing-query-fanouts
- Solis, Aleyda. “Google AI Mode’s Query Fan-Out Technique: What is it & How Does it Mean for SEO?” Aleyda Solis Blog, May 25, 2025. https://www.aleydasolis.com/en/ai-search/google-query-fan-out/
- Surfer SEO. “Ranking for Multiple Fan-Out Queries Dramatically Increases Your Chances of Getting Cited in AIOs (173,902 URLs Studied).” Surfer SEO Blog, 2025. https://surferseo.com/blog/query-fan-out-impact/
