Q2 2026

AI knows more brands than it mentions.

AI accurately described 96% of the brands we tested, yet 89% of the brands we measured never appeared in AI-generated answers. This report explores that gap and investigates the signals most strongly associated with AI visibility.

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Last quarter, we measured whether domain authority correlated with appearance in AI-generated answers. This quarter, we asked a different question:

Is there a relationship between how accurately AI understands a brand and how often it mentions that brand?

To that end, we measured two things across our cohort of brands: how accurately AI systems could describe each brand when asked, and how often AI mentioned those brands in AI-generated answers. Recognition rates were substantially higher than mention rates, which challenged our theory that recognition might influence AI mentions.

So we expanded our analysis to examine organic rankings, third-party web mentions, and other characteristics of a brand's presence on the web. This report presents the findings from that investigation and explains how they build on our Q1 research.

Michael Transon, Founder & CEO, Victorious
From our founder

Michael Transon

Founder & CEO, Victorious
Good research doesn't just answer questions. It raises better ones.

Last quarter, we found no meaningful relationship between domain authority and AI visibility. It wasn't the result we expected, but it was exactly the kind of result we hope to uncover.

Unexpected findings move research forward. They challenge our assumptions and point us toward the next hypothesis worth testing. This quarter, that led us to ask whether AI's ability to recognize a brand was related to its likelihood of mentioning that brand. The answer opened several new lines of inquiry.

Good research doesn't just answer questions. It raises better ones. That's the purpose of this quarterly report. Every edition builds on the last, following the evidence wherever it leads as we measure how AI systems discover and recommend brands.

I hope this report gives you a clearer understanding of what we know today, and encourages you to ask your own questions about what comes next.
Methodology

How we built this report.

We measured AI recognition and AI mention rates across a cohort of brands, then expanded the analysis to examine the signals most associated with AI mentions.

Cohort
0
Brands across five verticals
Recognition Dataset
0
Brands with evaluable AI responses
AI Platforms Tested
0
For the recognition measurement
Step 01

Measured AI recognition

We asked eight AI platforms to describe every brand in our cohort, then graded each response against the brand's own website: correct, vague, outdated, wrong, or not recognized.

Step 02

Measured AI mentions

We measured how often brands appeared in AI-generated answers to category prompts across five industry verticals, then compared mention rates to Step 1's recognition scores.

Step 03

Expanded the analysis

Recognition and mention rates didn't correlate as expected, so we expanded the analysis to organic rankings, organic traffic, third-party web mentions, and Knowledge Graph presence.

FINDING 01

AI accurately recognized most brands. It mentioned far fewer.

96% of brands were accurately described when AI was asked directly. 89% of those same brands never appeared in AI-generated category answers.

Recognition
0%
Accurately described by AI when asked directly
How we asked Describe this brand
What we measured Accuracy of description
What it reflects AI's understanding of a brand
Mention Rate
89%
Never appeared in AI-generated category answers
How we asked Category & buyer-oriented prompts
What we measured How often AI included the brand
What it reflects AI's selection during consideration
0%

of brands accurately described by AI never appeared in AI-generated answers to category prompts. Recognition and selection are distinct, measurable behaviors.

Our POV
Recognition rates answered one question and raised another. If AI understands most brands, what distinguishes the brands it includes in its answers?

Recognition varied by platform and vertical.

The combined 96% rate masks meaningful differences. Google AI Mode, Gemini, ChatGPT, AI Overviews, and Copilot all exceeded 83% across every vertical. Perplexity and Meta AI showed the widest variation particularly in SaaS and ecommerce, where Perplexity correctly recognized fewer than 55% of brands.

Recognition Rate by Platform & Vertical
PlatformEcommerceSaaSHealthcareLegalFinancial
Google AI Mode100%97%92%100%96%
Google Gemini100%97%92%100%93%
ChatGPT100%100%88%100%93%
Google AI Overviews96%96%87%100%96%
Copilot92%100%83%100%92%
Claude86%79%70%91%83%
Perplexity54%47%68%100%74%
Meta AI64%46%72%83%70%

Deeper shading indicates a higher recognition rate.

Finding 02 · Signals

The strongest signals came from beyond a brand's own website.

No single signal showed a sufficiently strong relationship with AI mentions on its own. Taken together, they describe the same underlying thing: overall brand prominence.

Signal Correlations with AI Mention Rate
Signal Relationship to AI Mentions What it tells us
Referring domains r = 0.49 Strongest relationship measured. Brands with more linking domains appear in AI answers more often.
Third-party web mentions r = 0.45 Brands referenced more broadly across the web are more likely to appear in AI-generated answers.
Semrush Authority Score r = 0.37 Moderate in a subset of 134 brands with sufficient AI mention activity. Market-wide, no meaningful relationship same as Q1.
Organic keyword rankings r = 0.33 Moderate. Brands with a broader organic footprint appear in AI answers more often.
Organic traffic r = 0.33 Moderate. Consistent with rankings visibility begets visibility.
Knowledge Graph presence No stable relationship Knowledge Graph presence alone does not predict AI mention rate.

*Correlation (r) measures the strength of the relationship between two variables on a scale from -1 to 1. Values closer
to 1 indicate a stronger positive relationship.

What this means

No single signal showed a sufficiently strong relationship with AI mentions on its own. Instead, the strongest relationships came from signals that reflect a brand's broader presence across the web. Third-party mentions, referring domains, authority, and organic visibility appear to capture different facets of that broader web presence. AI mentions aligned more closely with those combined signals than with any individual metric we measured.

Research notes: Authority Score & referring domain quality

Authority metrics require additional context.

Semrush Authority Score blends backlinks with signals like estimated traffic and spam indicators; referring domains is a direct count of unique linking websites. Only one held up as a signal across the full cohort.

Referring Domains
0.49
Relationship with AI mentions
Authority Score
0.37*
No meaningful relationship

*Based on a 134-brand subset with sufficient AI mention activity for correlation analysis.

Backlinks are a better indicator of the web prominence tied to AI mentions than Authority Score. Neither predicts AI mentions on its own.

Referring domain quality matters, but less than we thought.

Referring domains showed the strongest relationship with AI mentions of any signal we measured, so we looked at whether higher-quality referring domains strengthened that relationship further. They did, but only modestly.

Quantity

More referring domains, more mentions

Brands with more referring domains were consistently more likely to appear in AI-generated answers.

Quality

A modest additional lift

Higher-quality referring domains added a small independent relationship beyond link quantity, but broad third-party visibility remained the stronger signal.

Some brands earned links from highly authoritative sites yet still appeared infrequently in AI-generated answers — those links established authority in topics that didn't align with the questions AI systems were answering. This suggests that relevance matters alongside authority.

What this means

Building visibility across a broad network of reputable websites appears more important than pursuing only the highest-authority publications. High-quality backlinks still contribute, but they don't replace the value of broad, relevant recognition across the web.

Third-party mentions and AI mentions rise together.

Third-party web mentions — indexed pages that name a brand, excluding its own site — showed a clear relationship with AI mentions. We'll measure this benchmark again each quarter to see whether it holds as AI search evolves.

Indexed Third-Party Mentions → AI Mention Rate
Under 2K
3%
2K to 10K
25%
10K to 30K
47%
30K+
64%
At ~20,000 indexed third-party web mentions, brands reached roughly a 50% probability of being mentioned in an AI-generated answer.

Third-party web mentions measure the volume of indexed mentions, not their source or quality. A mention may come from a directory, review site, news article, community forum, or any other indexed web page outside the brand's own website.

Finding 03 · Industry Sources

The sources AI systems rely on differ by industry.

Legal services and health care responses cited a small group of authoritative sources. SaaS responses drew from more than 10,000 unique domains.

CITATION CONCENTRATION BY VERTICAL

24.8%
31.7%
Legal
Services
17.4%
28.1%
Healthcare/
Medical
15.5%
23.5%
Financial Svcs/
Insurance
14.5%
19.1%
Ecommerce/
Retail
7.1%
10.5%
SaaS/
Technology
Share of vertical citations (%)
Top 5 domains Top 10 domains
Vertical Top 5 share Top 10 share Unique domains cited
Legal Services24.8%31.7%1,659
Healthcare / Medical17.4%28.1%1,511
Financial Services / Insurance15.5%23.5%2,735
Ecommerce / Retail14.5%19.1%4,489
SaaS / Technology7.1%10.5%10,287
Top cited sources by industry

AI systems relied heavily on prestige legal directories and industry publishers. Vault, Chambers, and BCG Search accounted for nearly one-quarter of all legal citations.

Top sources
VaultChambersBCG Search

Government agencies, clinical institutions, and healthcare publications appeared most often.

Top sources
NIHAHRQMayo ClinicBecker'sU.S. News

Comparison sites and financial publishers dominated citations.

Top sources
NerdWalletForbesBankrateInsurance.comMoney

AI systems cited a broad mix of search platforms, communities, retailers, and business publications.

Top sources
GoogleRedditYouTubeWalmartAmazon

No single source dominated. AI systems drew from thousands of websites including community platforms, software review sites, professional networks, and analyst firms.

Top sources
G2RedditLinkedInGartnerGitHub
Finding 04 · Citation Patterns

AI systems rarely cite the brands they mention.

Of the 49,391 citations we analyzed across 5,830 AI-generated answers, 99.99% pointed to third-party websites rather than the brand's own domain. Only 4 of the brands in our cohort received a citation to their own website.

0%
Third-party sources
AI almost never links to the brand being mentioned.
0%
Brand's own domain
What we generated
0
AI-generated answers across 150 brands and 5 industry verticals
What we analyzed
0
Citations extracted and reviewed across six AI platforms

This pattern held across every platform we measured. ChatGPT and Google AI Mode cited a brand's own website just once or twice across more than 25,000 combined citations. Gemini and Google AI Overviews never cited a brand's own website in this study.

Publishing content on your own website is still important, but it is rarely enough on its own to earn citations in AI-generated answers. If you want to increase your visibility in AI search, your brand needs a presence in the third-party sources AI systems already rely on within your industry. As Finding 3 shows, those sources differ from one industry to the next.

Research notes: citation sources by platform

Citation sources by platform

PlatformCitationsThird-partyOwn-domain
Google AI Mode15,39799.99%0.01% (2)
ChatGPT10,48999.99%0.01% (1)
Google Gemini8,332100.00%0.00% (0)
Perplexity5,92099.98%0.02% (1)
Google AI Overviews5,082100.00%0.00% (0)
Copilot4,17199.98%0.02% (1)
Claude*0
Meta AI*0
Total (citing platforms)49,39199.99%0.01% (5)

*Claude and Meta AI returned no source citations in this collection round due to API limitations restricting web search for both platforms. Citation figures cover the six citing platforms only.

Finding 05 · Prompt Types

AI systems cite different sources at different stages of the buyer journey.

Problem awareness prompts and category research prompts produced different citation ecosystems and very different rates of brand mentions.

Problem Awareness
0%
of responses included at least one citation
Brand named per answer0.10%
Prompt typeEarly-journey problem questions
Example"How do I know if my business needs a lawyer?"
Category Research
0%
of responses included at least one citation
Brand named per answer1.29%
Prompt typeBuying-research questions
Example"What are the best law firms in the US?"

The source mix shifts with the buyer's stage.

AI systems drew from a fundamentally different set of sources depending on what the buyer was trying to accomplish. Category research prompts produced brand mentions more than twelve times as often as problem awareness prompts.

Problem Awareness Sources
  • YouTube
  • Government & institutional sites
  • LinkedIn & Reddit
  • Company educational content
  • Educational resources
Category Research Sources
  • Directories & rankings (Vault, Chambers)
  • Forbes, NerdWallet
  • Review & comparison sites
  • Industry comparison resources

What this means

Educational content and commercial content play different roles in AI visibility. Problem awareness content helps AI explain a topic and can earn citations before buyers begin evaluating providers. Category-focused content creates opportunities for AI to introduce your brand once buyers start comparing solutions.

Both matter, but they influence different moments in the journey.

Research notes: citation and naming behavior by platform

Citation and naming behavior by prompt type

Customer
Journey Stage
PlatformAnswersAnswers
w/ citation
Brands named
per answer
Category ResearchGoogle AI Mode1,018100.0%1.57%
Google AI Overviews743100.0%0.67%
ChatGPT1,01999.9%1.67%
Copilot1,01298.9%0.99%
Perplexity1,01888.0%0.98%
Google Gemini1,02086.4%1.67%
Meta AI*1,0000.0%2.00%
Claude*8980.0%1.22%
Problem AwareChatGPT708100.0%0.14%
Google AI Mode706100.0%0.14%
Google AI Overviews652100.0%0.00%
Copilot70399.4%0.14%
Perplexity70495.0%0.14%
Google Gemini70137.9%0.00%
Meta AI*6880.0%0.00%
Claude*6160.0%0.00%

*Claude and Meta AI citation data is incomplete due to API limitations.

Market Signals

The developments that shaped search this quarter.

Platform updates, algorithm changes, and industry developments that influenced the AI and organic search landscape during Q2 2026.

  • Mid-May 2026 (Google I/O)

    AI Mode reaches one billion monthly users

    Google announced that AI Mode now serves more than one billion monthly active users and previewed AI agents capable of completing multi-step research tasks, roughly one year after launch.

    Why it matters: AI Mode has become a mainstream search experience. Brands should account for it alongside traditional organic search.

  • March-May 2026

    ChatGPT citation patterns fluctuate

    ChatGPT's citation rate dropped sharply in March before partially recovering by May after OpenAI switched its default model.

    Why it matters: Don't assume every change in AI visibility reflects your own work. Platform updates can influence mention and citation rates independently of changes to your website.

  • May 21-June 2, 2026

    May 2026 Core Update

    Google rolled out its second core update of the year, with many practitioners reporting greater volatility than the March update.

    Why it matters: If you observed changes in organic visibility during our Q2 measurement window, this update is the most likely explanation.

  • June 3, 2026

    UK regulators reshape AI search

    The UK's Competition and Markets Authority required Google to give publishers meaningful control over whether their content appears in AI search experiences.

    Why it matters: Publishers are gaining more visibility into how AI search works and more control over where their content appears. Expect additional transparency to follow in the US.

  • June 3, 2026

    Search Console adds AI reporting

    Google introduced AI-specific impression reporting and publisher controls for AI Overviews and AI Mode in Search Console.

    Why it matters: You can now measure AI search impressions directly instead of relying solely on third-party tools or inference.

  • June 24-26, 2026

    June 2026 Spam Update

    Google released its second spam update of the year, continuing enforcement against scaled content abuse and other spam policy violations.

    Why it matters: Continue prioritizing original, trustworthy content. Google's investment in identifying low-quality and manipulative content shows no signs of slowing.

Market Signals

What the market is asking.

Recurring themes from over 200 client and prospect calls this quarter.

Q

If AI is actually sending people to my site, why doesn't that show up in my traffic?

A

It's common for AI platforms not to pass a referrer tag when they send a visitor to your site, so Google Analytics has no way to identify where that visit originated. When GA4 can't identify a source, it defaults to direct traffic the same category as someone typing your URL in by hand. Some portion of what your GA4 account currently reports as direct traffic is likely AI referral traffic that lost its identifying tag along the way.

An unexplained increase in direct traffic one with no matching campaign or brand push behind it is often a sign of this AI-driven traffic slipping through the cracks rather than a data anomaly to dismiss.

Measurement tools are starting to close that gap. Search Console is rolling out impression data for AI Overviews and AI Mode, so you'll be able to see directly when your pages appear there. GA4 has also added an AI Assistant channel built to capture referrals from ChatGPT, Gemini, Copilot, Claude, Grok, and DeepSeek. That channel only counts visits where the referral tag survived the trip, so it measures attributable AI traffic not the total demand AI is driving to your site. A low number in that channel more likely reflects a measurement gap than a lack of AI referrals. In most cases, the traffic is arriving; the attribution isn't catching up to it yet.

Q

I already have a strong presence on YouTube, Reddit, or social channels. Shouldn't that be helping me show up in AI?

A

Showing up in a platform's answers depends on being present in the specific sources that platform draws from when it builds a response and that source mix differs by platform and by industry. If your buyers research primarily through video, a strong YouTube presence is likely to matter more than in a category where research happens through written comparisons or forums. The breakdown of which platforms tend to pull from which channels, by industry, is covered in Finding 3. Use it to identify where your buyers already go for information, then confirm whether the AI platforms relevant to your category are pulling from those same sources.

Q

Why does my domain authority score look completely different depending on which tool I check?

A

The term most people use, "domain authority," actually refers to three different proprietary metrics that don't measure the same thing. Ahrefs calls its version Domain Rating built entirely from your backlink profile. Semrush calls its version Authority Score, which adds its own traffic estimates and spam signals. Domain Authority itself is a trademarked term belonging to Moz, a third separate scoring model. None of these come from Google, and Google doesn't publish or use any of them directly. A difference between your Ahrefs and Semrush scores reflects two companies working from different data sets and formulas not a measurement error.

Q

If I'm showing up in one AI platform, why aren't I showing up in another?

A

Visibility in one AI platform doesn't transfer automatically to another, because each platform retrieves its answers from a different pool of sources. Google's AI Overviews and Gemini draw on Google's own search index and Knowledge Graph. ChatGPT and Perplexity run their own retrieval process and cite whatever sources that process surfaces a separate pool from what Google checks. Appearing in one platform's results says relatively little about whether you'll appear in another, since the underlying systems aren't checking the same set of sources to begin with.

Looking Ahead

Questions we'll continue tracking.

Every quarterly report answers new questions and raises new ones. These are the areas we'll continue measuring as AI search evolves.

Do third-party mention thresholds remain stable?

Why it matters

If these thresholds hold, marketers gain practical benchmarks for evaluating brand visibility. If they change, it may signal that AI systems are recalibrating what qualifies as a prominent brand.

Does the early-journey citation ecosystem remain open?

Why it matters

An open citation ecosystem creates opportunities for brands to earn visibility through educational content before buyers begin evaluating solutions. If the ecosystem consolidates, those opportunities may become more competitive.

Are authority signals becoming more predictive of AI visibility?

Why it matters

One quarter establishes a correlation. Multiple quarters reveal whether those relationships are durable enough to guide long-term strategy.

Recommendations

What to do next.

Build broad third-party visibility.

The strongest relationships came from signals beyond your own website, especially referring domains and third-party mentions.

Tailor your strategy by industry.

The sources AI relies on differ by vertical. One citation strategy won't fit every market.

Match content to the buyer journey.

Educational content earns citations during problem awareness. Category-focused content creates opportunities for AI to introduce your brand later.

Take Action

Ready to build your AI search presence?

Our team works with marketing leaders who need to act with confidence. Let's talk about what the data means for your brand.