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Search is quietly undergoing one of the biggest structural changes since the birth of Google.

For two decades, SEO revolved around ranking for individual keywords.

But AI search doesn’t work like that anymore.

Instead of retrieving results for a single query, AI systems break your question into dozens of hidden searches behind the scenes.

This process is called query fan-out.

If you understand how it works, you can design content that gets cited inside AI answers, not just ranked in search results.

This newsletter issue explains:

Let’s dive in.

When a user asks an AI system a question, the system rarely runs just one search.

Instead, it expands the prompt into multiple related queries and retrieves results for each of them.

This is called query fan-out.

In simple terms:

One prompt → many hidden searches → one synthesized answer

For example, imagine someone asks:

“What’s the best way to save for retirement?”

An AI system might run queries like:

Each of these queries retrieves different sources.

Then the AI merges the information into one response.

This approach allows AI systems to:

The key takeaway for marketers:

Your page might be cited because it answers a sub-question, not the main query.

Traditional SEO was built on the assumption that:

1 query = 1 SERP

AI search breaks this model.

Now the process looks more like:

1 query → 20–100 subqueries → multiple SERPs → synthesized answer

This creates several major shifts.

AI systems look for passages that answer sub-intents, not pages optimized for a single keyword.

A page about “SEO basics” might be cited because it answers:

Even if it doesn’t rank #1 for “SEO basics.”

AI systems often extract specific paragraphs rather than evaluating the whole page.

That means:

become much more important.

Large studies show that many sources cited by AI answers don’t appear in the top Google results for the same prompt.

When you enter a prompt into an AI search system, the process usually follows four steps.

The system analyzes your prompt and extracts multiple sub-questions.

Example Prompt:

“Best project management tools for startups”"

Fan-out queries might include:

The AI runs many searches simultaneously.

Each query retrieves potential sources.

Results are ranked based on:

The AI merges the retrieved information into a single response.

Understanding this pipeline is crucial because it reveals something powerful:

Your content doesn’t need to rank for the original query to appear in the answer.

It only needs to rank for one of the hidden fan-out queries.

Instead of targeting a single keyword, a modern SEO strategy should focus on:

owning the entire query fan-out of a topic.

This means covering:

Think of your topic like a hub of questions rather than one keyword.

For example:

Topic: Technical SEO

Fan-out questions might include:

Your content should answer all of these.

Now let’s walk through a practical workflow using Ahrefs.

This demo shows how to turn a single keyword into a fan-out content strategy.

Open Ahrefs Keywords Explorer.

Enter a broad topic.

Example: “AI SEO”

You’ll typically see:

These variations approximate the fan-out space around the topic.

Look especially at:

These are proxies for the queries AI engines might generate.

Next, open:

Questions

This report shows natural language queries like:

These queries are almost identical to AI fan-out prompts.

Export them.

You now have the skeleton of the fan-out.

Next, filter by:

You want a mix of:

Example grouping:

AI SEO

These become supporting articles.

Now open the SERP overview in Ahrefs.

Look for:

These indicate the sub-intents AI systems are retrieving.

Example patterns:

Top pages may contain sections like:

These are clues to the fan-out structure.

Turn your findings into a content structure.

Example:

AI SEO: Complete Guide

Each article targets a fan-out query cluster.that goes even deeper into particular topics.

AI systems prefer structured passages.

Optimize your pages using:

Start sections with clear answers.

Example:

What is AI SEO

“AI SEO is the process of optimizing content so that AI search engines and generative systems can retrieve and cite it in synthesized answers.”

LLMs extract lists very easily.

These often appear in AI answers.

FAQ sections map perfectly to fan-out queries. Combine them with direct answers

Search engines and AI assistants increasingly rely on fan-out queries to construct answers.

Google has confirmed that AI systems may run multiple related searches across subtopics to generate responses.

For marketers, that means:

SEO is shifting from:

keyword optimization

to

topic coverage optimization

The winners will be those who structure content to answer entire clusters of questions, not just isolated queries.

If you remember only one idea from this issue, make it this:

AI search rewards topic coverage, not keyword targeting.

To compete:

Do this consistently, and your content has a far higher chance of being cited in AI answers.