In this AirOps webinar, Chris Long of Nectiv Digital joined host Josh Spilker to break down the new reality: AI systems don't just answer prompts, but fan out into dozens of layered searches, changing how your content gets discovered and cited.

Top 5 Takeaways

1. AI search relies on query fan-out, not single queries
   AI platforms like ChatGPT and Google Gemini break down prompts into multiple, layered searches, making the search landscape much more complex.
2. AI fan-out queries are longer and more varied than human searches
   LLMs (large language models) often generate detailed, multi-word queries—many with zero traditional search volume—pushing teams to rethink SEO tracking.
3. Structured content formats are critical for AI extraction and citation
   Using tables, lists, and Q&A blocks helps AI systems extract and cite your content accurately, increasing the chance of brand mentions.
4. Reviews, freshness, and comparisons dominate AI search patterns
   Content optimized for reviews, current years, and product comparisons is most likely to be retrieved and cited by AI.
5. Optimizing for Google and ChatGPT fan-out is largely overlapping
   Both platforms use similar extraction patterns, so optimizing for one typically benefits the other which will cons

Best Practices and Key Learnings

Chris's research into 60,000+ AI-generated searches reveals clear patterns that SEO and content teams can act on now. Here are the most important strategies for staying visible in AI search.

Understand query fan-out as the new search reality

AI systems break down prompts into multiple related searches, not just one. A single user prompt can trigger dozens of queries behind the scenes, each with unique variations and intent signals.

"So, query fan-out simply is, instead of doing a single search for a certain query, when you put in a prompt… it is going to perform multiple queries, right?" — Chris Long

This changes how you plan content coverage. Map out the different ways your core topics can be queried by AI, not just humans. Expect each prompt to generate several related searches, each with unique permutations. Use data from tools and APIs to reveal how your content is being accessed by AI.

Structure content for maximum AI extraction and citation

AI prefers content it can easily parse and summarize. The right formats increase your chances of being cited in AI-generated answers.

Chris's data shows tables are twice as likely to appear in ChatGPT results compared to Google Search. Why? They package information in a structured, scannable format that AI systems can extract and cite with confidence.

"Tables are two times as more likely to show up in ChatGPT than Google Search. The reason being is it nicely formats the content in a structured way that encapsulates the entire article." — Chris Long

Key actions to take:

• Use structured content formats like tables, lists, and Q&A blocks to help AI systems with AI extraction and citation, increasing the chance of brand mentions.
• Add FAQ sections to commercial pages to help AI summarize key information.
• Regularly update content with current years and clear comparison blocks.

Prioritize reviews, comparisons, and freshness

Chris's analysis revealed that reviews dominate AI search patterns across every category—products, software, local businesses, and more. AI consistently seeks out reviews and comparisons when conducting queries.

"Reviews is, like, it was by far the most common engram. It is looking for reviews on everything, for products, for software, for local businesses, I believe." — Chris Long

This means your optimization strategy needs to extend beyond your own site. Build and maintain a strong presence on third-party review sites relevant to your industry.

Create honest, detailed comparison pages that clarify how your product stacks up.

Refresh content regularly with up-to-date information and current-year references.

Track and analyze fan-out queries at scale

Traditional rank tracking doesn't cover the complexity of AI search. You need to segment and analyze fan-out queries to spot gaps and opportunities.

Start by segmenting fan-out query tracking in your rank tracking tools to monitor AI-driven performance. Use scalable data analysis to identify which topics and formats drive the most citations. Map fan-out queries to your content to find gaps and prioritize updates.

Optimize for both Google and ChatGPT together

Good news: the overlap in how AI platforms extract and cite content means you can streamline your SEO efforts. Chris's research shows that optimizing for one platform typically benefits the other.

Focus on content structures and topics that perform well across both platforms. Monitor changes in query patterns and adapt your optimization strategies accordingly. Use fan-out analysis to inform both your content creation and refresh plans.

Putting these insights into practice

Query fan-out isn't a future trend—it's how AI search works right now. Ignoring it means missing out on visibility and brand mentions in the places your audience is actually searching.

Start by auditing your top-performing content through the lens of fan-out queries. Which topics could AI systems query in multiple ways? Where are you missing coverage? Then, restructure your highest-priority pages with tables, lists, and FAQ sections that AI can easily extract and cite.

Finally, expand your optimization beyond your own site. Build your review presence, create honest comparisons, and keep content fresh with current-year references.

Win AI search with AirOps

Query fan-out is rewriting the rules for content and SEO teams. The teams that adapt now—structuring content for AI extraction, covering fan-out query variations, and building authority across platforms—will own visibility in AI search.

AirOps helps you do exactly that. Book a strategy session to see how we can transform your AI search performance.