Google’s AI Mode left me in awe when it launched last month. AI-based search combined with Google’s massive database — can search get any better?
But the content marketer side of me wasn’t all that happy. “Another AI engine to optimize for, and how?” I thought. If you’re reading this, I’m sure you must be thinking the same.
Luckily, Google didn’t leave us in the dark with this one.
According to their official documentation, the AI Mode uses query fan-out: a technique where the AI analyzes your query, breaks it into parts, finds answers across the web, and builds a response — instantly.
That’s one crucial piece of information that can help you optimize your content right and get featured in the AI Mode search results. How? I’ll explain all of it in this AI Mode Query Fan Out guide.
Let’s start with the basics.
What Is the Query Fan-Out Technique?
The query fan-out is a technique in which the AI deconstructs a user’s search into multiple related subqueries first — each targeting a specific intent, context, or entity. Then, it retrieves blogs, documents, and other content for each subquery to synthesize a final, comprehensive answer for the initial query.
Instead of relying on a single keyword match, it runs these subqueries in parallel, gathers the most relevant answers from various sources, and synthesizes them into one AI-generated response.
This technique is used both in the newly released AI Mode and the older AI Overviews. However, not all queries use the fan out technique. For example, a simple query such as “what’s 10+13?” might not require a fan out.
But for queries where there’s a scope to extract additional information, we can see why this technique is superior. Let’s take a simple query “moisturizers for dry skin.”
With the usual Google search, you’ll get:
- Product recommendations
- Product category filters
- Articles
The research part of finding information about the products is up to you. If you want to know anything about how a moisturizer helps or which ingredient is good, you’d have to do another search. Many times, you might not even know what questions or follow-up searches you need to do.
But the AI Mode, with its query fan-out technique, provides you all the necessary information up-front. Run the same search in AI Mode, and it not just gives you a basic list of products, it fans out the query.
Query Fan-Out Table: “Moisturizers for Dry Skin”
| Subquery | What It Addresses |
| What are the best moisturizers for dry skin in 2024 and 2025? | Provides curated, tested product lists from various trusted publishers |
| Which moisturizers are suitable for sensitive skin? | Identifies fragrance-free, non-comedogenic, hypoallergenic options |
| What ingredients are commonly found in moisturizers for dry skin? | Lists and explains key hydrating agents like ceramides, hyaluronic acid, glycerin |
| What are the benefits of specific moisturizers like La Roche-Posay, CeraVe, etc.? | Details product-specific ingredients and their functional benefits |
| Which moisturizers support the skin barrier? | Highlights formulas that include ceramides, peptides, and niacinamide for repair |
| What ingredients should people with sensitive skin avoid? | Warns against fragrance, drying alcohols, sulfates, parabens, and other irritants |
| What are humectants, occlusives, and emollients? | Defines ingredient categories and how each helps treat dry skin |
| Which moisturizers pair well with actives like retinol? | Notes compatibility with soothing or barrier-repairing formulas |
| Are there moisturizers that work well under makeup? | Calls out lightweight and fast-absorbing options like Clinique Moisture Surge |
| What are the common drawbacks of popular moisturizers? | Mentions potential irritation, breakouts, or fragrance concerns |
| How should you choose a moisturizer based on skin type and dryness severity? | Advises on selecting formulas by skin type and whether dryness is mild or severe |
| How should you test a new moisturizer? | Recommends patch testing to avoid adverse reactions |
| How often should you apply moisturizer? | Suggests twice daily or more, depending on dryness |
| When should you consult a dermatologist for dry skin? | Advises seeking professional help if symptoms persist or signal a condition |
Once it gathers information related to all these related queries, it’ll synthesise a combined response and deliver it. So, when you ask the AI Mode for “moisturizers for dry skin,” it gives you a list of products along with the ingredients and benefits:
Clicking on any of the products opens a Product Knowledge Panel with links for various online stores where you can buy it from.
Scroll down and you’ll find information about what ingredients to look for in a product, what to avoid, and what else to consider.
Basically, it tries to address all types of intent in a single query, anticipating the follow up question a user might ask.
How Google AI Mode Handles and Responds to Queries
Google AI Mode doesn’t just run the original query. It breaks that query into multiple thematic layers, each representing a different type of user intent or informational need.
Here’s how it typically splits:
- Functional attributes: What the user wants the thing to do. Think use cases, features, formats, ingredients, specs.
- Intent facets: What the user cares about. This includes factors like cost, durability, ease of use, brand comparisons, or verified reviews.
- Personal context: What makes this query unique to the user. Location, time of day, experience level, age group, even search history can play a role here.
This breakdown allows the AI to generate a broader range of subqueries — and then match each of them to the best available answers across the web.
Instead of relying on a single page to answer everything, Google’s AI Mode collects useful passages from many different sources and merges them into one summarized output.
Traditional search engines operate on a linear, rank-based model. Pages are listed in order, usually based on keyword matching, backlinks, and other authority signals.
But with AI Mode, the research burden on the user is less. That also means gaining visibility in such responses is tricky.
What does this mean for SEO? Let’s find out.
The SEO Implications of the Query Fan-Out Technique
For marketers and SEO professionals, there are some key SEO changes you need to keep in mind before designing your AI-first content strategies:
- Semantic coverage matters more than keyword matching: Google AI isn’t looking for exact terms — it’s looking for complete, intent-aligned answers across multiple subtopics. That means, instead of individual topics, it will prioritize websites that have complete keyword and topic clusters around a query.
- Surface-level content won’t qualify: If your content only addresses the main query without going into related angles, it won’t show up in AI Mode summaries.
- Every section must stand on its own: Google extracts responses at the passage level. Each paragraph needs to answer a specific subquery clearly and independently.
- Clarity and structure directly impact visibility: Well-organized, easy-to-skim content is more likely to be included. Use headings, clean formatting, and concise language.
Note: Google’s AI Mode citations are still difficult to track as there’s no data that shows up either in Google Analytics or GSC. To know more about how Google AI Mode works, read our AI Mode guide.
How to Optimize Content for Query Fan-Out Mode
You’re not just writing for users anymore — you’re writing for the AI that predicts what users want next. To show up in fan-out-driven results, your content needs to do more than answer a question. It needs to anticipate the full journey around it.
Here’s how to make that happen.
Think Like a Consumer
With the query fan out technique, Google’s AI Mode mirrors what a consumer wants.
It doesn’t just answer the query — it tries to predict what else the user might be wondering. That means your best bet is to think like a consumer yourself.
Start with a keyword you want to target. Now ask: If I were searching for this, what else would I want to know?
What doubts would I have? What comparisons would I consider? What details would help me decide?
Take the keyword “running shoes for flat feet.” A potential buyer might also wonder:
- What kind of arch support is best for flat feet?
- Are these shoes good for long-distance runs or just walking?
- Which brands make podiatrist-recommended options?
- How do I know if I have flat feet?
- Do these shoes help with knee or back pain?
- What’s the return policy in case they don’t fit?
List these questions. Then build them into your content — clearly and directly. The more of these angles you cover, the more subqueries your content will match. And that’s exactly how you earn visibility in AI Mode.
Analyze How the AI Model Thinks
One of the best ways to know what type of content to cover is to understand how the AI model thinks. But you don’t have to be a psychologist to do this.
Follow these two simple ways:
- Search your query in the AI Mode
This one’s pretty straightforward. Say you’re writing about “best running shoes for athletes.” Run this query through AI Mode and check what kind of topics it covers.
In this case, Google is categorizing the shoes based on several factors and also giving a list of specifications to consider. Include these details in your content.
- Check the “Thinking” pattern of Gemini
Google’s AI Mode uses Gemini 2.5 which can help you get insights into the query fan-out process. But simply using Gemini 2.5 won’t work. You need to use it within the AI Studio.
Once you open the Gemini interface, run the same query. And this time, instead of focusing on the response, check the “Thoughts” section of the AI model.
See how the model dissects your query, what type of follow up queries it asks itself, and what type of content it prefers. This will give you a fair idea of how to structure your content.
Use relevant tools to maintain semantic depth
Another way to find relevant keywords and maintain semantic depth is by using tools that surface real user questions and trending search behavior.
Start with a tool like Answer The People. Enter your target keyword, and you’ll get a map of questions people are actually asking around that topic — what, why, how, which, and more. These aren’t just keyword variations — they’re potential subqueries Google’s AI could use in fan-out.
Pair this with Google Trends to identify search patterns and rising queries related to your topic. If you’re writing about “vegan diets,” for example:
Covering these related queries builds out your semantic network — and gives AI more reasons to pull your content into its response.
Ask AI to Fan Out Keywords You Are Targeting
You can also simply ask AI to help you fan out a query to get ideas on what topics to cover.
Use the prompt: Help me fan out the query “[keyword/topic]” Generate a list of different related queries and subtopics and group them based on relevance.
Here, I asked ChatGPT to fan out our earlier example: “vegan diets.”
Many of these queries appear to be questions a user would naturally ask after the initial query. Analyze them and determine which of these topics would make a natural and useful addition to your content.
Check ‘People Also Ask’ and Related Searches
Google already gives you a peek into how it expands queries — you just have to pay attention.
The “People Also Ask” (PAA) box is one of the clearest signals of what Google considers related intents. These follow-up questions aren’t random. They reflect real user behavior and often align with the subqueries generated during AI Mode’s fan-out process.
The same goes for the “Related Searches” section at the bottom of the results page. It shows you what users often explore next — and which adjacent queries Google groups together with the original.
Use both as research tools. Scan them for patterns. Are the same questions appearing across similar keywords? Are there gaps your content isn’t addressing yet?
If you see a question show up in PAA repeatedly, that’s not optional — it’s a must-cover topic. Including answers to these questions makes your content more complete and helps you match Google’s internal logic more closely.
The best part? These insights are free, live, and based on real-time behavior — straight from the SERP.
Use Reddit and Other Social Platforms
If you want to know what real users are asking — not just what they’re searching — head to platforms like Reddit, TikTok, YouTube, and Quora.
Reddit, in particular, is a goldmine for understanding raw, unfiltered user concerns. Search your topic (e.g., “dry skin moisturizer”) and look at the threads in skincare subreddits. You’ll find questions like:
- “Is CeraVe or Cetaphil better for flaky skin in winter?”
- “Can I layer moisturizer under sunscreen?”
- “Which moisturizer doesn’t pill under foundation?”
These are real-world subqueries that might not show up in keyword tools — but they absolutely reflect the kind of angles Google’s AI could include in a fan-out response.
Social platforms also help you identify emerging vocabulary, trends, and concerns. A TikTok video about “slugging” or a YouTube review of a trending ingredient like squalane can clue you in on what’s gaining traction — before it shows up in traditional tools.
Use this content as a signal. If people are asking it, and AI is listening, your content should be answering it.
SEO Best Practices for Succeeding in Query Fan-Out Mode
Here’s how to align your content strategy with the way Google AI Mode actually works — by focusing on structure, breadth, and semantic precision.
- Optimize for subqueries, not just the main keyword
Don’t build your page around a single phrase. Instead, use the queries from the above steps to map out the full set of related questions. Think of each article as a content hub, where each section answers a distinct sub-intent. This increases your chance of being featured in Google’s synthesized response — even if you’re not ranking #1 overall. - Prioritize broad but to-the-point topic coverage
Cover as much of the topic as needed — but do it efficiently. Avoid fluff and repetition. Each paragraph should address a unique aspect of the user’s journey. The goal is to offer enough context for the AI to pull from, while keeping every section focused and extractable on its own. - Build keyword and topic clusters to support authority
The query fan-out technique draws from multiple URLs, not just one. So, publishing just one article on a topic won’t be as helpful. Instead, build supporting content around the core topic and link internally between them.
This creates a semantic structure that AI models recognize — and gives your domain stronger topical authority.
Limitations in Current Tools for the Query Fan-Out Technique
For all its impact, query fan-out still happens behind closed doors. Google doesn’t reveal which subqueries are triggered, how they’re weighted, or which content gets used in the final AI output. That makes it harder to reverse-engineer it with traditional SEO tools.
Most third-party platforms still focus on keyword tracking, rank positions, and SERP features — but they’re not built to monitor real-time query expansion or passage-level relevance. This means there’s a gap between how SEO is measured and how visibility actually works in AI Mode.
To work around this, start using the tools available now:
- Use Gemini or ChatGPT to simulate subquery generation. Prompt them to expand your primary keywords and predict related questions a user might ask.
- Scan platforms like Reddit, TikTok, Quora, or forums to understand how people actually phrase their questions — and what kinds of answers resonate. These UGC environments are goldmines for discovering natural subquery formats.
- Use tools like Writesonic to understand how your brand is performing across AI search engines, especially AI Overviews.
Final Thoughts: AI Mode Query Fan Out Technique
Google’s AI Mode doesn’t just reward high-ranking pages — it rewards high-context content. With the query fan-out technique, every search turns into a web of micro-questions. If your content doesn’t address them, it won’t show up — no matter how well-optimized it seems on the surface.
The good news? You don’t need to guess your way through it.
Tools like Writesonic give you visibility into how your content is performing across AI engines. From identifying prompts where your brand is performing well to analyzing the general sentiment of how your brand is portrayed, GEO helps you optimize for where search is actually heading.
If you’re serious about showing up in AI-generated answers, GEO is the tool you’ll want in your stack.
