AI Overviews (AIOs) are rewriting the rules of search. If you’ve watched Google roll out AI-generated summaries at the top of results pages, you’ve probably noticed two things:
- They push traditional blue links further down.
- They’re shifting user behavior from “click to explore” toward “scan and accept.”
For marketers who’ve spent years fighting for top-10 rankings that drive leads, this feels like their traffic is being stolen. But look closer. The sites cited in AIOs are often (but not always) the same ones already ranking for the query. Which means ranking still matters, but the playbook has changed.
Enter Query Fan-Out
Here’s the piece most people miss. When someone types (or speaks) a query, an AI engine doesn’t just evaluate that single string of words. It fans out into multiple variations and refinements of the question. Think of it as the model breaking a search into a cluster of “possible intents,” each slightly different but related.
For example:
- Query: “best accounting software for small business”
- Fan-out variations: “affordable accounting software,” “QuickBooks vs competitors,” “do I need payroll included,” “how to choose software for freelancers.”
AI then blends these variations into an overview, citing sources across the cluster.
That means you’re not competing for one keyword anymore. You’re competing to be relevant across an entire field of semantically related queries.
Why This Complicates Things
Classic SEO strategy often went as follows: pick the right keyword, build a page, optimize it, and track rankings. That’s obviously over-simplified but was often the way it was done.
Query fan-out complicates that by:
- Diluting the “one keyword, one page” model.
- Expanding the competitive set – you’re now competing with sites covering adjacent questions you didn’t think to target.
- Raising the bar on information depth and satisfaction, because AI looks for content that resolves multiple angles of a user’s need, not just a single phrasing.
Where the Opportunity Lies
This isn’t just a challenge, it’s a chance to do better marketing. If you know your customers, their pain points, and their journey, you can build content that anticipates these additional search queries.
Instead of thinking “How do I rank for best accounting software for small business,” ask:
- What are the jobs-to-be-done (JTBD) for my customer here?
- What pain points trigger this search?
- How do those needs evolve across the buying journey?
Marketers who can answer those questions will create content that covers not just the primary query, but the fan-out queries AI engines consider. That’s how you get cited in AIOs. It is also the way it should have been done all along because that’s how you create good, useful content.
Next Steps for Marketing Teams
Here’s how to start adjusting your strategy:
- Map the journey
Break down your customer’s process step by step. For each stage, list their jobs-to-be-done (JTBD) and likely questions. - Audit content through the customer’s eyes
Does your content answer their questions with depth and clarity, letting them benefit from your expertise? Or are you still publishing shallow posts chasing single keywords? - Evaluate from an LLM perspective
Would your content satisfy an AI model tasked with summarizing answers? That means clear structure, semantic richness, and comprehensive coverage. - Iterate continuously
Keep learning from your clients and refining your content. The models evolve; so should your content.
The Bottom Line
Don’t think of Query fan-out as something you need to work around, think of it as a reflection of how people really search. Customers don’t think in keywords; they think in problems, comparisons, and next steps. AI search engines mirror that by widening queries into clusters.
If you can align your content with those clusters by focusing on customer needs and information satisfaction, you don’t just protect traffic – you position your brand as the authoritative source AI overviews view as reliable.
It’s a new search landscape, and this is how you stay visible.
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