Topical Authority in AI Search: Why LLMs Favor Focused Brands

A common belief I hear from business owners is this: “ChatGPT and Google’s AI only mention the biggest brands, so there is no point trying.” It is easy to see why people think that. Ask an AI assistant about running shoes or phones, and the same famous names keep coming up.

But look closer and a different pattern appears. In many categories, the brands that AI answers keep naming are not simply the largest. They are the ones most clearly connected to one subject, across their own site and across the rest of the web. A focused brand gives an AI system a simple, consistent story to repeat. A scattered brand gives it nothing to hold on to.

In this guide, I will explain in plain words why topical depth matters in AI search, what the 2025 and 2026 studies actually show, and a practical plan to tie your brand to your topic. If you need the foundations first, read my main guide on building topical authority step by step. This post focuses only on the AI side.

How AI answers pick sources when one question becomes many

When you type a question into Google’s AI Mode or trigger an AI Overview, the system does not just run your exact words as one search. Google’s own documentation on AI features and your website says both features “may use a ‘query fan-out’ technique.” In simple terms, that means the AI quietly runs several related searches across subtopics, then pulls supporting pages from each one before writing its answer.

When Google launched AI Mode, it described the idea this way, as quoted by Aleyda Solis:

“breaking down your question into subtopics and issuing a multitude of queries simultaneously on your behalf”

— Google’s description of AI Mode, quoted in Aleyda Solis, Google AI Mode’s Query Fan-Out Technique

ChatGPT and other assistants that search the web work in a broadly similar way. I have covered the mechanics, with examples, in my guide to ChatGPT query fan-out, so I won’t repeat them here. What matters for this article is the effect on which pages get picked.

Ahrefs measured that effect. In its March 2026 study 38% of AI Overview citations pull from the top 10, it analyzed 863,000 keyword results pages and 4 million AI Overview URLs. Only 37.9% of cited URLs also ranked in the top 10 for the original query, down from about 76% in its 2025 study. And 31.0% of cited URLs sat outside the top 100 altogether. Ahrefs suggests the likely reason is that citations are coming from the results of the fan-out sub-queries, though it notes Google does not show those queries, so this is an informed explanation rather than proof.

“AI Overviews have shifted, and ranking for the user’s exact query is no longer a guarantee of visibility.”

— Ahrefs, Update: 38% of AI Overview Citations Pull From The Top 10

Let me put that plainly. Ranking for one keyword is no longer enough. The AI is shopping across a whole set of related questions. The site that has a good page for many of those questions has many more chances to be picked.

Why a cluster gets cited more often than one great page

Here is a hypothetical example to show how this plays out. Imagine someone asks an AI assistant: “Is a heat pump worth it for an old house in a cold climate?” The assistant might break that into sub-questions like the ones below. I made these up for illustration; real fan-out queries are not published.

Likely sub-question	Page a focused heating company could have	Page a general home site usually has
How do heat pumps perform below freezing?	Cold-climate heat pump performance guide	One paragraph in a general article
Do old houses need insulation before a heat pump?	Insulation and heat loss checklist for older homes	Nothing specific
What does a heat pump cost to install?	Cost breakdown by home size	Generic price range
What rebates exist?	Rebate and grant guide for the region	Outdated national list
Heat pump vs gas boiler running costs	Running cost comparison with a worked example	Comparison article on many topics

The focused company has a strong candidate page for five out of five sub-questions. The general site has maybe one or two. Even if the general site is far bigger, the focused site simply shows up in more of the searches the AI runs. And when the same brand appears again and again across sub-questions, it becomes the natural brand to name in the final answer.

Ahrefs makes the same point in its topical authority guide: because AI systems split one query into several, a cluster that covers more subtopics appears for more of them. Its example is a single Healthline page on magnesium glycinate that ranked for 2,500 keywords on Google and showed up for 473 queries in AI Overviews, 279 prompts on ChatGPT and 200 on Perplexity. That is what deep coverage looks like from the AI side.

The practical lesson: a topical map of your subject is no longer just an SEO planning tool. It is a list of the sub-questions an AI will ask on your customer’s behalf.

Brand-topic association: what AI systems learn about you

Fan-out explains how your pages get picked. But AI answers also name brands, often without linking to anyone. That depends on a different thing: how strongly the web connects your brand name to your topic.

Think of how a language model learns. It reads huge amounts of text and notices which words appear together. If thousands of pages say “Brand X” next to “accounting for restaurants,” the model learns that connection. In SEO terms, your brand becomes an entity (a recognized “thing”) linked to a topic. I explain entities in more depth in entity SEO.

Ahrefs tested which factors line up with brands appearing in AI Overviews. Its May 2025 study, An Analysis of AI Overview Brand Visibility Factors, looked at 75,000 brands and found these correlations (Spearman, where 1 would be a perfect match):

Factor	Correlation with AI Overview brand mentions	What it tells you
Branded web mentions	0.664	Being talked about is the strongest signal
Branded anchors	0.527	Links that use your brand name help
Branded search volume	0.392	People searching for you by name matters
Domain Rating	0.326	Link strength helps, but less
Referring domains	0.295	Number of linking sites helps a little
Backlinks	0.218	Raw link count is the weakest of these

Ahrefs also found that brands in the top quarter for web mentions averaged 169 AI Overview mentions, while brands in the bottom half averaged between 0 and 3.

“Putting it another way, if your brand sits in the lower 50% of web mentions, you’re essentially invisible to AI systems.”

— Ahrefs, An Analysis of AI Overview Brand Visibility Factors (75K Brands Studied)

Two honest notes. First, correlation is not cause. Big, well-known brands have more of everything, so these numbers partly reflect fame. Second, this study counts mentions in general, not mentions about a topic. Still, combined with what we know about how models learn, my reading is this: mentions that pair your name with your topic are the ones that build the association you want. A hundred mentions in unrelated listicles teach an AI far less than twenty in the places your buyers read. For the full list of factors, see my post on AI brand visibility factors.

What the 2026 AI Visibility Index says about focused brands

The biggest dataset so far is Semrush’s expanded 2026 AI Visibility Index, released on June 26, 2026. It covers 126 million US prompts from January to April 2026 across ChatGPT, Gemini, Google AI Mode and AI Overviews, in 22 industries. A few findings stood out to me:

• Only 36 brands held a top-100 visibility spot on all four platforms every month. Semrush calls them the “Universal 36,” and they include YouTube, Google, Reddit, Amazon and Walmart. So yes, giants dominate the very top.
• Concentration varies a lot by industry. The top three brands held 82.9% of visibility in News and Media, but only 41.4% in Finance and 42.2% in Industrial. Semrush says the flatter categories “may offer greater opportunities.”
• Mentions and citations are different things. On Gemini, the overlap between brands mentioned and domains cited can be as low as 30%, according to the release.
• Focus and consistency show up even at brand level. Patagonia kept a steady score throughout the study, which Semrush links to consistent descriptions across specialist outdoor sites.

“Patagonia, for example, maintained an AI visibility score of approximately 79–80 throughout the study period, supported by consistent descriptions across sources including OutdoorGearLab, REI, Switchback Travel, GearJunkie, and Reddit.”

— Semrush, Semrush Releases Expanded 2026 AI Visibility Index

PPC Land’s coverage of the index (June 30, 2026) adds a useful detail: six specialist outdoor-gear sites, led by Reddit, generated over 65,000 Patagonia mentions, which Semrush said was more than all the traditional top-tier media in the dataset combined. It also notes Patagonia has no sub-brands taking a meaningful share of its mentions, while Apple has 18.

I read this as strong support for the topical idea. The sources that shaped Patagonia’s AI visibility were specialist sites about its exact topic, describing it the same way. That is brand-topic association in action. One caveat: this is a press release and a news summary, not a full methodology paper, so I treat the numbers as direction rather than hard science.

Focused brand vs generalist brand in an AI answer

Here is how I explain the difference to clients. Picture the same mid-sized company in two versions.

Signal	Focused version	Scattered version
Website content	40 deep pages on one subject, all interlinked	40 pages across eight loosely related subjects
How others describe it	“The payroll tool for restaurants”	“A business software company”
Where it is mentioned	Restaurant trade sites, hospitality forums, review sites	Random listicles and press release sites
Fan-out coverage	Has a page for most sub-questions on its topic	Has one page on each topic, none complete
Likely AI behavior	Named when people ask about restaurant payroll	Rarely named for anything

Nothing in the second column is “bad.” It just gives the AI no clear reason to pick the brand for any one question. That is the core of why focused brands do well. If you have drifted into many subjects, my sibling guide on whether off-topic content hurts SEO explains how to decide what to keep.

Worked example: tracking 40 prompts for a niche software brand

This is a hypothetical example with invented numbers, to show how I would measure progress.

A company sells scheduling software for dental clinics. It picks 40 prompts that real buyers might ask, split into four subtopics of 10 prompts each: staff rota planning, patient reminders, no-show reduction and software comparisons. It runs each prompt in ChatGPT, Gemini and Google AI Mode once a month and records whether the brand is mentioned or cited.

Subtopic	Pages on site (month 0)	Mentions in month 0 (out of 30 checks)	Pages on site (month 6)	Mentions in month 6 (out of 30 checks)
Staff rota planning	1	2	8	11
Patient reminders	2	3	7	9
No-show reduction	0	0	6	7
Software comparisons	1	1	3	4
Total	4	6 of 120 (5%)	24	31 of 120 (26%)

Two things to notice in this made-up example. The subtopics that got the most depth moved the most. And the comparison subtopic moved least, because AI answers about “best software” lean heavily on third-party review sites, not your own pages. That part needs mentions on other sites, not more blog posts. Also remember AI answers change from run to run, so always look at totals across many prompts, never at one answer. For tooling, see my guide on tracking your brand’s visibility in AI search, and for how to judge progress across a whole cluster, see how to measure topical authority.

A 90-day plan to tie your brand to one topic in AI answers

Here is how I would do it for a small or mid-sized business:

1. Write one sentence that says what you are. For example: “We are the payroll software for independent restaurants.” Use the same wording on your homepage, About page, social profiles and directory listings. Consistency is what Patagonia had.
2. Pick one core topic and list 30–50 sub-questions. Use People Also Ask, Search Console queries, sales calls and the questions you get by email. These are your likely fan-out queries.
3. Audit what you already have. Mark each sub-question as “answered well,” “answered thinly” or “missing.”
4. Fill the gaps with focused pages. One clear question per page, with a direct answer near the top, then detail, examples and your own experience. Link every page to a hub and to two or three related pages.
5. Earn mentions where your topic is discussed. Trade publications, niche podcasts, industry forums, review platforms and “best of” lists in your field. Ask that they describe you with your one sentence. My guide to digital PR for AI visibility covers how.
6. Get links from sites about your topic. A link from a relevant trade site does double duty: it helps rankings and it reinforces the topic connection. See why topically relevant backlinks matter more than metrics.
7. Track 30–50 prompts monthly. Record mentions and citations per subtopic, as in the example above.
8. Refresh, don’t just add. Update pages when facts change. Old prices or outdated stats are a quick way to lose citations to a fresher source.

Notice what is not on the list: special AI tags, secret files or “AI-only” pages. Google’s AI features documentation says there are no additional requirements or special optimizations needed to appear in AI Overviews or AI Mode. The same SEO basics apply. If you want a beginner-level refresher, our free lesson on AI Overviews and AI Mode covers them.

What topical authority can’t do for you in AI search

I want to be fair about the limits, so you set the right expectations:

• It won’t beat the giants on broad questions. In concentrated categories like news or consumer electronics, a small brand is unlikely to replace the top names for “best phone.” Aim at narrower questions where you can be the clear specialist.
• Model knowledge lags behind. When an assistant answers from its training data instead of a live search, it reflects what the web said months ago. New brands take time to “arrive.”
• Answers vary. The same prompt can give different brands on different days. Judge trends, not single screenshots.
• Your own site is only part of it. The Semrush and Ahrefs data both point to what others say about you. Content alone, without mentions, has a ceiling.
• Nobody outside the AI companies knows the exact rules. Everything here is based on documentation and correlation studies. I treat it as direction, not hard science.

Questions marketers ask about topical authority and AI answers

Do I need a separate strategy for ChatGPT and for Google’s AI?

Mostly no. Both reward deep, clear coverage and a brand that the web connects to a topic. The sources they lean on differ, so check which sites each platform cites in your niche and focus your outreach there. My guide on how to rank on ChatGPT covers the ChatGPT-specific side.

Does publishing more pages always help AI visibility?

No. More pages only help if each one answers a real sub-question well. Thin pages made to cover keywords can hurt the whole site in Google, and they give AI systems nothing worth quoting.

Are unlinked brand mentions useful?

Yes. In Ahrefs’ study, branded web mentions, linked or unlinked, had the strongest correlation with AI Overview brand mentions. A mention in the right context helps teach the connection between your name and your topic.

How long until a focused strategy shows up in AI answers?

Expect months, not weeks. Live-search answers can pick up new pages fairly quickly once they rank, but changing how models describe your brand takes sustained mentions over time.

Should a brand with several product lines split into separate sites?

Usually not. It is often better to make each product line a clear, deep section with its own hub, and to keep your brand story consistent. Splitting resets your links and mentions.

Where to start if AI assistants don’t mention you yet

In brief: AI assistants favor brands they can describe in one clear sentence, with pages that answer many related questions and mentions from places that discuss the topic. That is topical authority, seen from the AI side.

So start small. Write your one-sentence positioning. Pick one topic. Map its sub-questions, fill the gaps, and earn a handful of mentions on sites your buyers trust. Then track 30–50 prompts every month and let the trend tell you what is working.

If you would like help building that cluster and the mentions around it, our SEO team does this work every day. Get a free quote and we will show you where your brand stands in AI answers today and what to fix first.

Our complete topical authority guide series

This article is part of a series. Start with the main guide, then read the parts you need:

1. Topical Authority: What It Is and How to Build It Step by Step
2. How to Create a Topical Map for Your Website (With a Free Template Layout)
3. How to Measure Topical Authority (Without a Magic Score)
4. Building Topical Authority on a New or Small Website
5. Topical Authority vs Domain Authority: What's the Difference?
6. Topical Authority in AI Search: Why LLMs Favor Focused Brands (you are here)
7. Content Depth vs Breadth: What to Publish First to Build Authority
8. Internal Linking for Topic Clusters: Rules That Build Topical Authority
9. Topically Relevant Backlinks: Why Link Context Matters More Than Metrics
10. Does Off-Topic Content Hurt SEO? When to Publish Outside Your Niche

Sources for this AI search topical authority guide

1. Topical Authority: What It Is, How Google Measures It, and How to Build It — Ahrefs, June 2026
2. AI features and your website — Google Search Central
3. Update: 38% of AI Overview Citations Pull From The Top 10 — Ahrefs, March 2026
4. An Analysis of AI Overview Brand Visibility Factors (75K Brands Studied) — Ahrefs, May 2025
5. Semrush Releases Expanded 2026 AI Visibility Index, Analyzing 126 Million AI Search Prompts — Semrush, June 2026
6. Semrush: 36 brands win AI visibility everywhere — PPC Land, June 2026
7. Google AI Mode’s Query Fan-Out Technique: What is it and How Does it Mean for SEO? — Aleyda Solis