How to rank and get cited in Google AI Mode
If you ask Google's AI Mode a question, it mostly doesn't search for that question. According to Google's own documentation, it uses a "query fan-out technique, breaking down your question into subtopics and issuing a multitude of queries simultaneously." Its Deep Search mode takes the same approach further, issuing "hundreds of searches" to assemble a single answer.
So by the time AI Mode replies, it has run a fan of queries you never saw and stitched the response together from whatever those queries returned.
Ranking here isn't a page winning a query. It's being retrievable across a whole topic's worth of hidden sub-queries, and being quotable once you're retrieved.
What is Google AI Mode?
AI Mode is Google's dedicated AI search experience, a separate, conversational tab where you ask a question, get a synthesized answer with links, and keep going with follow-ups. It runs on a custom version of Gemini and Google's ranking systems, and it's where the fan-out goes the furthest.
Speaking of Gemini, both that app and AI Overviews tend to blur together with AI Mode, although they’re not the same thing:
- Gemini is the standalone assistant app.
- AI Overviews are the summary box that appears above the blue links on an ordinary results page.
- AI Mode is the immersive, multi-turn tab you enter on purpose.
They share Google's plumbing, but they don't produce the same answers. Our team found a median eight-point difference between a brand's best and worst-performing Google surface, and only about 35% overlap in the brands each one names. Optimizing for one isn’t optimizing for all three, and AI Mode, with the most citations and the widest net, plays by its own rules.
Query fan-out: The mechanism that rewrites the rules
When you ask AI Mode a question, it breaks the question into subtopics, runs multiple searches at once, and then reasons across the results to build an answer. Deep Search scales that to hundreds of queries and a fully cited report.
The consequence is a different competition. You're no longer trying to win one query; you're trying to be one of the sources that surface across a cloud of related ones. A page that nails the head term but says nothing about the twelve sub-questions around it loses to a topic that covers the whole cloud. In Answer Engine Optimization (AEO) terms, every search is now long-tail, whether or not the user typed a long-tail query.
You can't cover a fan-out you can't see, and most of it is invisible by default. In order to surface them, you can:
- Read the model's own reasoning. AI Mode and Gemini can show the sub-questions they generated for a prompt. It's the most direct look at a real fan-out, but it's manual and won't scale past a handful of prompts.
- Mine adjacent questions. People Also Ask, and tools like AlsoAsked, expose related queries that approximate parts of the fan-out.
- Model it from real data. Profound's Query Fanout Estimator predicts how AI turns a given prompt into multiple searches, based on actual fan-out data. That's the version that scales to hundreds of topics.
Win the fan-out: Own the topic, nail the passage
Covering a fan-out has two jobs. Breadth makes you relevant to more of the sub-queries AI Mode generates; depth gives it useful, self-contained passages it can draw on when assembling the answer. Miss either one and you become a partial source: broad but shallow content doesn't give the model much worth using, while a brilliant answer to one narrow question won't help with the rest of the fan-out.
Own the whole topic
To build breadth:
- Map the sub-query cloud first. Start with the questions surrounding the topic, not a list of keywords. What would someone need to know before, during, and after making a decision? Those questions become your coverage map, and often your content architecture.
- Build a hub and cluster. Use a strong overview page to establish the topic, then create focused pages for the major sub-questions. Interlink them so the relationship between the concepts is explicit. One page can establish relevance; a connected body of useful pages demonstrates depth.
- Span the full intent range. The same topic can fan out from “what is X?” to “how does X work?” to “X vs. Y,” “alternatives to X,” and “best X for Y.” Cover informational, evaluative, and commercial intent rather than optimizing everything around the query closest to the bottom of your funnel.
- Find the gaps, not just the keywords. Look at the questions an AI-generated answer needs to resolve and ask where the existing sources are thin, vague, outdated, or repetitive. Those gaps are often more valuable targets than another page aimed at a high-volume head term.
- Connect the answers. Don't treat each sub-question as an isolated SEO page. Explain the relationships between them, link to supporting evidence, and make it obvious how one answer leads to the next. A topic is stronger when its concepts reinforce one another.
- Treat coverage as living. Fan-outs aren't fixed. New products, regulations, competitors, terminology, and user concerns create new sub-queries. Revisit your coverage map periodically and fill in the gaps, rather than assuming the topic was “done” when the first cluster shipped.
Be the passage that gets extracted
For depth:
- Answer first. Put the direct answer in the opening sentence or two, then explain the reasoning, caveats, and evidence. Don't make an AI system—or a human—dig through five paragraphs to discover your point.
- Make every section stand on its own. A passage may be encountered without the paragraphs immediately before and after it. Define the subject, use specific nouns rather than ambiguous pronouns, and include enough context that the answer still makes sense when separated from the page.
- Give claims something to stand on. Specific facts, examples, comparisons, original data, and clearly attributed evidence are more useful than generic assertions. If you're making a claim an AI answer might repeat, make it easy to verify.
- Structure for retrieval and comprehension. Use headings that describe the actual question being answered, short paragraphs, tables for genuine comparisons, numbered lists for processes, and clear definitions for specialized terms. Good structure helps readers navigate and gives systems clearer units of meaning to work with.
- Don't make the answer text-only. If the topic is better demonstrated through a video, product walkthrough, forum discussion, chart, or another format, cover it there as well. The goal is not to turn every asset into an article; it's to make your expertise available in the formats people—and AI search systems—can discover and use.
- Get your technical AEO in order. Server-render the content that matters, keep critical claims out of JavaScript-only elements, use crawlable internal links, and make sure robots.txt and other access controls aren't blocking important content. The best passage in the world can't contribute to an AI-generated answer if Google's systems can't reliably access it.
- Write for the sentence, not the page. Before publishing, ask: If this paragraph appeared by itself in an AI answer, would it still be accurate, useful, and attributable? If the answer is no, tighten the passage. That's the level at which fan-out visibility is ultimately won.
Feed the sources AI Mode cites, including Google itself
AI Mode cites more than Gemini, and it cites differently. Its answers lean into social and user-generated sources and, increasingly, into Google's own surfaces. Our data found that google.com surged 8.4x to become AI Mode's second-most-cited domain, driven almost entirely by Business Profiles and Product Knowledge Panels appearing as interactive cards within the answer. For a lot of queries, a Google-hosted card is what the user sees before they click anything, if they click at all.
That changes where the off-page work goes. The Reddit and YouTube presence that matters for Gemini is important here too, at even higher citation depth, and the playbook for both is in our Gemini guide. What's specific to AI Mode is that your Google-hosted profiles are now front-line real estate:
- Treat your Google Business Profile like an AI landing page. Complete every relevant field—category, services, attributes, hours, description, photos—and keep it current. These aren't just details for someone browsing Maps; they're structured signals Google can surface directly when AI Mode answers local and service queries.
- Keep the reputation layer healthy. Reviews give AI Mode first-party-on-Google evidence about how customers experience a business. Don't try to manufacture that evidence. Encourage genuine reviews, respond to legitimate criticism, and resolve recurring issues. A profile with a strong, current body of customer feedback is a much better source than one that has gone stale.
- Make your product data machine-readable and boringly accurate. Product Knowledge Panels depend on Google's understanding of the product and the information available through its product and Merchant ecosystem. Keep names, prices, availability, images, attributes, identifiers, and other product data synchronized and accurate. If Google's product record is incomplete or wrong, the card can be incomplete—or the wrong product can win the slot.
- Don't ignore Google's entities. Make sure the basics agree across your website, Business Profile, Merchant data, major directories, and other authoritative sources: the same name, location, products, category, and key facts. AI Mode has to resolve what a business or product is before it can confidently use it in an answer.
- Prioritize the surfaces that can replace the click. A citation isn't always a blue link to your site. It can be a business card, product panel, map result, review signal, or other Google-hosted element. Optimize those surfaces with the same seriousness you give your organic pages—because increasingly, they are where the answer begins.
- Move first in exposed verticals. Our data showed hospitality, home services, restaurants, real estate, and healthcare experiencing particularly strong disruption from Google-hosted cards. If you're in one of those categories, profile completeness and data accuracy aren't housekeeping tasks; they're part of your AI-search distribution strategy.
Measure AI Mode visibility: The attribution black hole
AI Mode is the hardest Google surface to measure and the easiest to lose track of. It collapses clicks, and it hides inside the metrics you already have. Search Console reports AI Mode activity within the web-search bucket, so it can't tell you whether AI Mode named you in an answer that produced no click. And clicks are the wrong scoreboard anyway.
Pew Research found that when a Google AI summary appears, users click a result 8% of the time, compared with 15% without one, and only 1% click a link within the summary; about two-thirds of searches now end with no click at all. AI Mode's full-page, answer-first experience only pushes those numbers further.
So the metric that matters isn't traffic. It's whether you're in the answer. That means tracking share of citation across the fan-out and triangulating rather than waiting for a clean clickstream that no longer exists:
- Citation share on AI Mode specifically, for the prompts your buyers use, tracked continuously.
- Which sources and competitors AI Mode assembles alongside or instead of you.
- How AI Mode represents you, sentiment and accuracy, not only whether you appear.
- Self-reported attribution on demo and signup forms, to catch the influence that never produced a click.
- Sales call notes where buyers mention researching you via AI.
Take the lead in Google’s AI Mode with Profound
Everything above is a lot of continuous work: mapping a fan-out you can't see, covering a whole topic, keeping Google-hosted profiles up to date, and measuring a surface built to hide its own impact. We designed Profound, the #1 agentic marketing platform for AI search, to run that loop.
It starts with clearly seeing the fan-out and the surface. Profound tracks AI Mode as its own engine, and its Query Fanout Estimator predicts how a prompt explodes into sub-queries from real data, so the hidden cloud becomes a content map. Answer Engine Insights shows the sources and competitors AI Mode assembles for the prompts you care about, and flags where it has you wrong.
Because fan-out coverage is repetitive work, we offer much of it as prebuilt agent templates you can run or tailor:
- An AI Mode Theme & Content Brief Builder that reverse-engineers the themes AI Mode surfaces for a topic and writes the brief.
- A SERP Content Gap Analyzer and a Cannibalization Checker to plan a cluster that covers the fan-out without competing with itself.
- A Chunk-Level Citation Audit that scores each passage the way an answer engine would, alongside heading, schema, and content-refresh agents.
- PDP and FAQ generators for the product and commercial queries where AI Mode leans on Google's cards.
- Brand Health reports that track citation share and sentiment on the topics you're trying to win.
And when nobody has time to watch a surface this fast-moving, that's the case for AI Marketer (AIM), Profound's background agent for marketing. It runs the loop for you: watching your AI Mode visibility, sentiment, and accuracy, flagging what changed, and turning it into scoped, ready-to-deploy projects your team approves, and Agents execute.
Fan-out only gets wider. Deep Search already runs hundreds of queries for a single answer, and the surface keeps citing more, not less. The brands that map their sub-query clouds and cover them now will be the ones AI Mode keeps assembling later. The rest will keep ranking for queries that nobody searches for.
Start winning AI citations today. Book a demo with our team.
How to rank in Google AI Mode FAQs
Is AI Mode the same as AI Overviews?
No. AI Overviews are the AI summary that appears above the regular search results; AI Mode is a separate, conversational tab you enter deliberately. Both use query fan-out, but AI Mode takes it furthest and cites the most, and a brand's visibility can differ between them by a median eight points. Optimizing for one doesn't guarantee the other.
Does my existing Google ranking still matter?
Yes, as the eligibility layer. If Google can't crawl and index you, you can't be assembled into an answer. But ranking a single page for a single term isn't enough anymore, because fan-out rewards topic coverage over any one position. Classic SEO gets you in the running; covering the fan-out is how you win it.
How do I know if I'm showing up in AI Mode?
Not from Search Console, which folds AI Mode into web search. You can spot-check by running your priority prompts in AI Mode and seeing who it assembles, but that doesn't scale or track change over time. Measuring citation share on AI Mode as its own surface takes a dedicated tool.
Will optimizing for AI Mode help me in Gemini too?
Partly. They share Google's infrastructure, so crawlability and entity clarity help across the board. But they source answers differently: AI Mode leans on UGC and Google's own cards, while Gemini cites references sparingly, so the sources diverge.