As consumers increasingly turn to ChatGPT, Gemini, Claude and Google AI Mode to research products and services, marketers are beginning to ask a different question. It is no longer just about where a brand ranks on search. It is whether AI mentions the brand at all. New research suggests that AI visibility is emerging as a distinct marketing metric, one that could influence discovery, reputation and even purchase decisions.
For more than two decades, marketers have relied on a familiar set of digital metrics. Website traffic, search rankings, impressions, click-through rates and share of voice have served as benchmarks for measuring brand visibility. Today, another metric is quietly finding its place on that dashboard.
The question is deceptively simple. When a consumer asks ChatGPT for the best running shoes, Gemini for a project management tool or Claude for a hotel recommendation, does the AI mention your brand?
It is becoming an increasingly relevant question as conversational AI moves from being a novelty to a discovery platform. Unlike traditional search engines that present users with pages of links, AI assistants often summarise answers into a handful of recommendations. In many cases, consumers never see a long list of competing brands. They see only those that the model considers most relevant.
That shift is forcing marketers to rethink what digital visibility means in an AI-first environment.
The timing is significant. Google's AI Mode has crossed one billion monthly active users globally, according to the company's latest announcements, while OpenAI recently said ChatGPT has surpassed 700 million weekly active users. These numbers indicate that AI-powered interfaces are no longer experimental products. They are becoming mainstream destinations for research, comparison and product discovery.
As AI-generated answers replace traditional search journeys for many users, being absent from those responses could mean missing an entirely new layer of customer consideration.
Industry observers increasingly describe this as the next evolution of search rather than its replacement.
"What we're seeing is another discovery layer," says Kipp Bodnar, Chief Marketing Officer at HubSpot. "Brands now have to think about how they are represented both in traditional search and within AI-generated answers."
The challenge is that AI systems work differently from search engines. Search rankings are influenced by keywords, backlinks and page authority. Large language models, by contrast, synthesise information from multiple sources before generating a response. They may cite a company's website, refer to independent reviews, draw from news coverage or rely on widely discussed public information.
For marketers, that means visibility is becoming less about owning every keyword and more about earning recognition across the wider digital ecosystem.
Recent research suggests this visibility is far from evenly distributed.
A June 2026 study examining more than 100,000 AI-generated responses across over 100 brands found that globally recognised brands appeared in nearly three out of four relevant AI answers. Mid-sized established brands were mentioned less than half the time, while smaller niche brands appeared in only around one in ten responses. The findings highlight how AI systems often reinforce existing brand familiarity, particularly in broad consumer categories.
Yet brand size alone does not guarantee visibility.
Another study analysing AI brand exposure across different industries found considerable fluctuations over time. Brands that dominated AI recommendations one month experienced sharp declines the next, even without significant changes to their products or marketing activity. The research suggests that AI visibility remains dynamic as models update, new content enters the web and user behaviour shifts.
For marketers accustomed to relatively stable SEO rankings, that unpredictability introduces an entirely new challenge.
The rise of AI-generated recommendations is also changing how brands think about authority.
Traditional SEO rewarded websites that accumulated backlinks and optimised content around search intent. AI models appear to place greater weight on broader digital signals.
Research analysing more than 75,000 brands found that mentions across the wider web showed a much stronger relationship with AI visibility than conventional SEO indicators alone. References on platforms such as YouTube, trusted news publications, expert reviews and discussion forums appeared to influence whether brands surfaced in AI-generated responses.
In other words, AI models seem to favour brands that are being talked about rather than simply those publishing the most content.
That finding aligns with another large-scale study conducted across leading AI platforms, including ChatGPT, Claude, Gemini and Perplexity.
Researchers examined more than one million citations generated by these models and found that approximately 94 percent originated from unpaid sources. Around 82 percent came from earned media, while roughly a quarter referenced journalism.
Perhaps even more striking was the freshness of those citations. Nearly half pointed to content published within the previous year, with the highest citation rates occurring during the first week after publication.
For brands, this suggests that sustained visibility across credible publications may increasingly influence how AI systems understand and describe companies.
That represents a notable shift from the era when marketers focused primarily on optimising owned websites.
Google itself appears to recognise this changing landscape.
Earlier this year, the company introduced dedicated Search Console reporting for AI Overviews and AI Mode, allowing publishers and brands to monitor impressions, pages and visibility generated specifically through Google's AI experiences.
The move effectively acknowledges AI-generated discovery as a reporting category separate from traditional search performance.
Marketing technology vendors are responding in a similar way.
Several platforms now offer dashboards measuring AI mentions, AI citations, AI share of voice and AI sentiment, reflecting growing demand from brands seeking to understand how often they appear in AI-generated conversations.
Importantly, these metrics are not interchangeable.
A mention indicates that an AI model includes a brand within its answer. A citation refers to the source the model attributes while generating that answer. A company might receive frequent mentions without its own website being cited, while another could be cited for factual information yet never emerge as one of the recommended brands.
That distinction is becoming increasingly relevant as marketers attempt to measure influence beyond clicks.
Consumers are also changing the way they use AI.
Adobe's latest retail research found that nearly four in ten online shoppers have already used generative AI while researching purchases, while more than half expect to do so regularly in the near future. During the same period, referral traffic from generative AI platforms to retail websites grew dramatically, reflecting AI's expanding role in the purchase journey.
The implication is clear. AI is no longer simply answering questions. It is beginning to shape commercial decisions.
And unlike conventional search, where dozens of brands compete on the same results page, AI often narrows the field to just a handful of names.
That makes every mention count.
One reason AI visibility is proving difficult to manage is that it is far less predictable than traditional search rankings. A website may hold the top position for a keyword on Google for months, but the same brand could appear inconsistently across AI responses depending on how a question is phrased, which model is being used and what sources the model considers most authoritative at that moment.
Research by AirOps illustrates this volatility. The study found that only about 30 percent of brands maintained visibility across consecutive AI-generated responses, while just one in five remained consistently present across five separate prompts. Brands that were both mentioned and cited were significantly more likely to reappear than those that were simply referenced without attribution. The findings suggest that marketers cannot rely on a handful of prompt tests to judge AI performance. Visibility has to be measured over hundreds or even thousands of interactions to establish meaningful trends.
That inconsistency has led marketers to shift their attention from rankings to what many now call AI share of voice. Instead of asking where a webpage appears, brands are increasingly tracking how often they are recommended, compared or cited when consumers ask broad category questions.
This becomes especially important because AI systems compress choice.
A conventional search page may display ten organic results, shopping ads, maps, videos and forum discussions. By contrast, an AI assistant may recommend only three brands when asked for the best CRM software, electric SUV or skincare routine. Brands outside that shortlist may receive no visibility at all despite ranking well on traditional search engines.
The narrowing of options changes the competitive landscape.
It also raises another question that marketers have rarely had to ask before: why does AI choose one brand over another?
Current research points towards authority rather than optimisation alone.
Studies from Ahrefs and Similarweb indicate that AI models rely heavily on signals gathered across the wider internet rather than exclusively from company websites. Mentions in credible news publications, independent reviews, YouTube discussions, analyst reports, academic research and community forums appear to strengthen a brand's likelihood of appearing in AI-generated responses.
Adelle Kehoe, Director of Product Marketing at Similarweb, describes the emerging pattern simply.
"Authority, not just scale, is emerging as the differentiator."
That observation is becoming increasingly relevant for marketers who have traditionally invested most of their resources in owned channels.
Instead of focusing solely on publishing more webpages, brands may need to consider whether trusted third parties are talking about them consistently and accurately.
This growing dependence on external validation is reflected in another large study conducted by media intelligence platform Muck Rack.
After analysing more than one million citations generated by ChatGPT, Gemini, Claude and Perplexity, researchers found that earned media dominated AI citations. Approximately 82 percent of referenced material originated from unpaid editorial coverage, while only a small proportion came directly from brand-controlled assets. Journalism alone accounted for roughly one quarter of all cited sources.
The study also highlighted the importance of recency.
Half of the cited content had been published within the previous eleven months, while newly published material received the highest citation rates during its first week online. For brands, that finding suggests visibility within AI models may increasingly depend on maintaining a consistent stream of credible third-party coverage rather than relying solely on evergreen website content.
The implications extend well beyond consumer brands.
In B2B markets, where purchase decisions often begin with research rather than advertising, AI-generated summaries are becoming a common starting point.
A procurement manager asking ChatGPT to compare cybersecurity platforms or recommend ERP vendors may receive only a handful of company names. Those recommendations could shape an initial shortlist before a buyer ever visits a company website.
That shift places greater importance on executive thought leadership, analyst recognition and industry media visibility.
Professional identity is becoming another signal.
Research cited by Axios found that LinkedIn has emerged as one of the most frequently referenced domains for professional queries across major AI platforms. According to Profound, citations from LinkedIn have increased substantially over recent months as AI systems increasingly draw from executive profiles, company pages and professional expertise.
For companies, that means an executive's public profile is no longer simply a recruitment tool. It may influence how AI systems describe an organisation's expertise and credibility.
The issue becomes even more significant when information is inconsistent.
Semrush recently surveyed hundreds of marketing and SEO professionals and found that only around one in five organisations currently have a fully integrated strategy for AI search alongside traditional SEO.
The same study revealed that more than one-third believed competitors appeared more frequently than their own brands in AI-generated responses. Nearly one-third also reported instances where AI described their company inaccurately or presented an incomplete picture of their products and services.
Leigh McKenzie, Director of Online Visibility at Semrush, believes fragmented communication is partly responsible.
"Brands have historically managed their websites, PR, social media and search separately. AI pulls information from all of those places simultaneously."
That creates a different communications challenge.
Rather than optimising individual channels independently, organisations increasingly need consistency across every public-facing source that AI systems may reference.
Visibility, however, is only one side of the equation.
Reputation is becoming equally important.
BrightEdge's latest analysis found that negative sentiment appears in a relatively small proportion of AI-generated brand mentions. Yet because AI responses are repeated across thousands or millions of similar queries, even a small percentage can influence public perception at scale.
The study found that Google AI Overviews were somewhat more likely to surface controversy related to lawsuits, recalls or regulatory actions, while ChatGPT more frequently highlighted product limitations and value comparisons.
Jim Yu, Founder and Executive Chairman of BrightEdge, argues that brands should not focus exclusively on being mentioned.
"The conversation has shifted from simply earning visibility to understanding the context in which brands appear."
That distinction matters.
Being recommended as an industry leader creates a very different impression from being cited primarily in connection with customer complaints or product issues.
As marketers begin monitoring AI visibility, many are discovering that frequency alone provides only part of the picture.
Context, sentiment and source credibility matter just as much.
This growing complexity explains why technology providers are introducing dedicated AI visibility dashboards.
Google has added AI-specific reporting within Search Console, while several SEO platforms now measure AI mentions, citations, sentiment and share of voice separately from conventional search metrics.
Although the methodologies differ, the overall direction is clear.
AI visibility is gradually becoming a measurable performance indicator in its own right.
It is also becoming one that extends across multiple departments.
Marketing teams need consistent messaging.
Communications teams need credible media coverage.
Product teams need accurate documentation.
Executives need active professional profiles.
Customer experience teams need to address recurring concerns that AI models may repeatedly surface.
The responsibility no longer sits within SEO alone.
For marketers, perhaps the biggest takeaway is that AI has not replaced search. Instead, it has added another layer between consumers and brands.
People still visit websites, compare reviews and make their own decisions. But increasingly, those journeys begin with a conversation rather than a search box.
Whether that conversation includes a particular brand is becoming an increasingly important question.
The available evidence suggests there is no single tactic that guarantees inclusion.
Instead, AI models appear to reward brands that demonstrate authority across multiple trusted sources, maintain accurate and consistent public information, earn regular editorial coverage and continue contributing useful expertise to the wider digital ecosystem.
For years, marketers competed to appear on the first page of search results.
Today, they face a different challenge.
When AI reduces an entire category to three recommendations, being absent from that answer may become just as significant as losing a top search ranking.
The race for visibility has not disappeared.
It has simply moved into the conversation.
Disclaimer: All data points and statistics are attributed to published research studies and verified market research. All quotes are either sourced directly or attributed to public statements.