This post is sponsored by Victorious. The opinions expressed in this article are those of the sponsors.
A year into the transition to AI search, the marketing industry is brimming with confidence about AI visibility factors. But we’ve seen very little data to support commonly held views.
We wanted to see what correlation we could find between general search performance and AI attribution and citations. So we designed a study to see if we could uncover evidence-based recommendations from the data.
Study Guide: Comparing Traditional vs. AI Search Performance
In order to compare how brands perform in traditional search versus AI search, we need a dataset that captures both signals for the same companies at the same time.
We built it in four stages.
Step 1: Determine the Product Set.
We selected a diverse range of 177 product representatives across five categories: healthcare, SaaS, financial services, ecommerce/retailing, and legal services.
Step 2: Capture the AI Visual Signal.
For each product, we tested specific instructions for all eight AI platforms: ChatGPT, Perplexity, Gemini, Google AI Overview, Google AI Mode, Microsoft Copilot, Claude, and Meta AI. That gave us 107,011 AI responses to analyze.
For every response, we recorded two things: whether the platform named the product (mention), and whether it linked to the product’s domain as a source (citation).
Step 3: Pull Biological Performance Data.
For these 177 brands, we tracked the organic level performance of the site on Semrush for the first quarter of 2026, including traffic trends and authority scores.
Step 4: Cross-Reference the two data sets.
We joined AI visibility data with organic data so that each brand has three common measures: mention rate, citation rate, and Authority Score. That structure let’s look at the relationship between the signals at the general level and the appearance of AI, and that those factors were more or less related in different specific areas.
Why We Track Quotations and Quotations Separately
A single metric doesn’t capture AI visibility, so we tracked both mention rate and citation rate as separate signals. For example, a product can be mentioned often and cited often, or cited often and rarely. Tracking both separately, rather than collapsing them into a single “AI visibility” result, ended up being among the nuances we could have drawn from different specifics.
Finding 1: Most brands don’t have AI names at all
Of the 177 brands in our dataset, only 18 had any AI mention rate above zero in Q1 2026. That means 89.8 percent of the brands we tested were not very active in search AI across the eight platforms we measured. They were not mentioned. Brands did not appear in relation to answers, such as sources, or examples.
This is in contrast to many current discussions of the industry, which treat AI visibility as a race already underway. Our data show a very different picture. With a very large number of products, the race has not yet begun.
The fact that only 18 of the 177 brands in our survey registered any mention of AI at all shows that brands willing to take the visibility of AI seriously will now be competing against a small number of vertical players, not against an entire category.
Finding 2: Patterns of AI Exposure Differ by Position
When we break the data down vertically, three distinct patterns emerge.
Mentioned and Cited: Healthcare, SaaS & Financial Services Products
Brands within these three categories were frequently mentioned and referenced, but for different reasons. Healthcare products benefit from clear business identifiers such as names, locations, specialties, and network organizations, which reinforce the signals used by AI platforms to assess expertise and authority. SaaS brands are often featured on third-party forums such as G2, Reddit, and LinkedIn, where products are discussed by users and reviewers. Financial Services benefits from a strong editorial media presence on platforms like MarketWatch, Bankrate, and NerdWallet, which are common sources that AI platforms turn to for financial questions.
Financial Services was also the only stand where citations slightly exceeded mentions, suggesting that AI platforms trust content less than trusting specific brands at the moment.
In each case, emerging brands have some AI platforms that can attach brand identity: to structured data, third-party verification, or editorial input. Brands that don’t show are usually missing one or more of those.
More Talked Than Said: Ecommerce & Retail Brands
Ecommerce posted the largest gap in our dataset. AI platforms recognize these brands but pull their source material elsewhere, usually marketplaces, aggregators, and review sites rather than product domains.
For these brands, recognition comes from market presence and consumer familiarity. The biggest challenge for ecommerce products is giving AI platforms content that should be quoted on their domain, instead of leaving the field to Amazon, Reddit, and review aggregators.
Cited But Rarely Mentioned: Legal Services
Legal services posted the opposite pattern as ecommerce products. AI platforms always find content from legitimate sites, but rarely give credit to the company behind the article.
Bridging that gap means creating business signals that link a piece of content back to a known firm.
Findings 3-4
Each AI platform draws on a different set of sources.
ChatGPT, Perplexity, Gemini, and Copilot show preferences for certain types of content. The full report breaks down the metrics in question by platform and vertical, so you can focus on the AI platforms your customers are using.
Personalization may include an early appearance of AI.
Google’s Personal Intelligence update pulls signals from a user’s Gmail and Photos into AI Mode responses, biasing results toward brands the user has already encountered. If that effect holds, brands that win the user’s first AI interaction on a topic can consolidate their visibility faster than late entrants. The full report goes into what we’re looking at in Q2 to test this.
Key Takeaway
If you do not remove anything else from this data, remember that you have not lost the first submission benefit. With only 18 of the 177 brands we measured for profit talking about AI search, there’s still white space in your rankings waiting to be searched.
You can read the full search report for Q1 2026 on our site.
Gain Your Search Profit with AI
Photo Credits
Featured image: Photo by Victorious. Used with permission.
Posted Photos: Photos by victory. Used with permission.
