Semrush, the search and generative engine optimization platform now operating under Adobe ownership, published the expanded 2026 AI Visibility Index on June 26, 2026, scaling its analysis from an initial 2,500 prompts to 126 million United States AI search queries collected between January and April. The report quantifies a pattern many marketing teams have suspected but struggled to prove: brands that treat search engine optimization and artificial intelligence visibility as one connected discipline report meaningfully better results than those that manage the two separately.

The finding sits inside a companion survey conducted alongside the prompt analysis. Among organizations that fully integrate SEO and AI visibility into a single workflow, 81% reported increased traffic or leads from AI platforms, according to Semrush. Among organizations that manage the two areas as separate functions, only 36% reported the same outcome. The 45-point gap between those two groups represents one of the report's clearest practical takeaways for marketing departments deciding how to structure their teams.

Consumer behavior helps explain why that structural choice matters. Traffic arriving at United States retail websites from AI-powered sources surged 1,324% between October 2024 and May 2026, according to Semrush, drawing on data supplied by Adobe. The travel sector recorded an even steeper climb: AI-referred traffic to travel sites rose 2,215% across the same nineteen-month window. Those figures describe a channel that barely existed in most marketing plans two years ago and now represents, in some categories, a larger share of discovery traffic than many teams have infrastructure to track.

That tracking gap is precisely what the report's companion survey set out to measure, and the numbers are stark. Some 45% of marketing leaders said they cannot accurately measure their brand's visibility within AI-generated answers, Semrush found, while only 9% said they have the tools needed to track every relevant metric across the AI platforms their customers use. In other words, fewer than one in ten marketing organizations can currently see the channel that Adobe's own traffic data shows is growing fastest.

What the index measures

The AI Visibility Index examines how four major AI search surfaces, ChatGPT, Google Gemini, Google AI Mode, and Google AI Overviews, mention, cite, and represent brands across 22 industry verticals. The expanded version released June 26 built directly on an earlier iteration of the same index that Semrush launched in September 2025, though this version scales the underlying dataset by roughly five orders of magnitude, moving from 2,500 sampled prompts to 126 million.

PPC Land's earlier report on this same index detailed the headline structural finding: of more than 1,200 brands Semrush tracked across the four platforms, only 36 maintained top-100 visibility on every platform during every month of the study window. Semrush refers to that group as the Universal 36, and it includes companies such as YouTube, Amazon, and Walmart, brands with broad consumer reach and an established role in helping shoppers complete comparison or transaction tasks.

The distinction between being mentioned and being cited runs through much of the report's methodology. Being mentioned in an AI-generated answer does not necessarily mean a brand's own website supplied the underlying source material; a company can appear frequently in AI responses while a competitor, a review site, or a community forum supplies the actual citation the AI system relied on. On Gemini specifically, the overlap between mentioned brands and cited domains can fall as low as 30%, according to Semrush, meaning that seven in ten domains the platform cites belong to entities other than the brand being discussed. That gap forces a two-front competitive posture: brands must earn enough relevance to be mentioned at all, while separately building the structured, credible content that AI systems select as supporting evidence.

Platform-level citation behavior varies sharply

The four platforms analyzed do not behave uniformly, and the differences carry direct implications for where a marketing team should concentrate its optimization effort. ChatGPT cites an average of 15 sources per response and draws heavily on community and reference platforms including Reddit and Wikipedia. Gemini, by contrast, cites an average of just 3 sources per response, pulling from a narrower pool that also includes Reddit, Wikipedia, and YouTube.

That fivefold difference in citation volume helps explain why a brand might perform strongly on one AI platform while remaining nearly invisible on another; a company whose visibility strategy depends on breadth of citation, rather than depth, will naturally fare better on ChatGPT's wider net than on Gemini's narrower one. Semrush's own recommendation, echoed in the report, is that brands measure AI visibility platform by platform rather than treating the category as a single undifferentiated channel.

Case studies point to third-party validation

Two brand case studies included in the underlying research illustrate different paths to consistent AI visibility, though PPC Land's prior coverage has already detailed both in depth. Patagonia maintained an AI visibility score in the high 70s to low 80s throughout the study period, a consistency Semrush attributes less to paid media spend than to a network of third-party outdoor-gear review sites, including OutdoorGearLab, REI, Switchback Travel, and GearJunkie, alongside sustained discussion on Reddit. Shopify presented a more balanced pattern between mentions and citations, a rarity the report notes, since most brands skew toward one or the other rather than achieving parity between the two metrics.

Those examples support a broader conclusion the report draws about how brand narratives now form. A company's AI narrative is no longer shaped solely by its own website and brand-controlled marketing materials, according to Semrush. AI platforms increasingly rely on customer reviews, community discussions, independent publishers, retailers, and industry-specific sources to understand and describe a given brand, which means public relations, community management, and earned media now function as inputs into AI visibility in ways that traditional SEO teams have not historically had to account for.

Industry concentration varies by category

Competitive dynamics differ substantially by industry, the study found, and that variation may determine how much opportunity exists for a brand to gain ground. In News and Media, the three most visible brands accounted for 82.9% of total category visibility, according to Semrush, while Consumer Electronics showed a comparable concentration, with the top three brands representing 76.9% of visibility in that category.

Finance and Industrial verticals told a different story. The top three brands in Finance accounted for just 41.4% of category visibility, while the top three in Industrial represented 42.2%. Those two categories, the least concentrated in the study, may offer greater room for mid-sized or emerging brands to build AI visibility over time than categories where a handful of dominant names already command the overwhelming majority of AI attention.

An executive framing built around brand narrative

Rachel Thornton, chief marketing officer of Adobe Enterprise, framed the stakes of the report in terms of brand consistency across every digital touchpoint a customer might encounter. "Your AI narrative is becoming the decisive entry point to your customer experience," Thornton said, according to the announcement. "But the new reality is, your customers are both people and AI agents. Minimizing brand drift to ensure accuracy and consistency across every digital touchpoint is now the starting point for securing visibility. This requires new content strategies, stronger data foundations, and organization-wide governance."

Andrew Warden, vice president of marketing at Adobe and former chief marketing officer of Semrush, offered a related but distinct emphasis, pointing toward organizational structure rather than content strategy alone. "AI is now intrinsic to the default search experience, and brands need to adapt. The name of the game is Brand Visibility," Warden said. "The foundations of SEO are critically important in creating trust signals for AI, but visibility now depends on how consistently a brand reinforces its narrative across digital channels. Marketing teams need to redesign how they work across SEO, content, communications, data, and brand governance to compete in this new environment."

Both quotes point toward the same underlying argument that runs through the report's integration statistic: SEO fundamentals remain necessary but are no longer sufficient on their own. A brand can rank well in conventional search results while still performing poorly across AI-generated answers if its content, third-party citations, and cross-channel narrative are not managed as a coordinated system.

How the framework separates discovery from credibility

Adobe's own brand visibility materials, published alongside the Semrush data, describe a three-part structure for how AI systems evaluate a brand before recommending it to a user. The first layer concerns whether AI can find a brand at all, a function of the underlying authority and relevance signals a domain has accumulated. The second layer, which Adobe frames as clarity, asks whether AI understands the brand correctly once it has been found, since a citation built on outdated or inconsistent information can misrepresent a company even when it succeeds at generating a mention. The third layer, authority, determines whether AI will actually recommend the brand once it understands what the brand offers, rather than simply acknowledging that the brand exists.

That layered framing maps onto the mention-versus-citation distinction the underlying prompt data revealed. A brand can clear the first layer, appearing in AI conversations, without clearing the second or third, meaning it never accumulates the structured, citable content that would make an AI system comfortable recommending it over a competitor. Adobe's materials describe this progression as requiring coordinated investment across owned content, third-party validation, and technical structuring of product or service information rather than a single optimization tactic applied in isolation.

Context: a year of accelerating AI search measurement

The June 26 index arrives roughly seven months after Adobe completed its acquisition of Semrush, a deal PPC Land reported in detail when it was announced on November 19, 2025. Adobe paid $12 per share in an all-cash transaction valuing Semrush at approximately $1.9 billion, a deal explicitly framed at the time around helping brands manage visibility across large language models and traditional search engines simultaneously. The AI Visibility Index 2026 represents one of the first major joint research outputs published under that combined ownership structure, with contributions from executives at both companies.

Semrush's own prior disclosures illustrate why the measurement gap the new survey documents has been building for some time. The company revealed in October 2025 that it had nearly tripled its own AI share of voice, from 13% to 32% in a single month, according to PPC Land's earlier coverage of that disclosure, after discovering that ChatGPT recommended every one of its competitors but never mentioned Semrush itself, despite the company's own blog content being cited hundreds of times by the same platform. That episode illustrated, at the scale of a single company, the same mention-versus-citation gap the 2026 index now quantifies across more than 1,200 tracked brands.

Separate Semrush research published earlier in June examined how business-oriented content performs inside AI citation systems specifically. That study, covered by PPC Land on June 9, 2026, analyzed 89,000 LinkedIn URLs cited across ChatGPT Search, Google AI Mode, and Perplexity, finding LinkedIn ranked as the second most-cited domain in AI search responses at an 11% citation rate, trailing only Reddit. The findings complement the broader industry-wide patterns the AI Visibility Index 2026 documents, since both point toward third-party and community platforms carrying disproportionate weight in how AI systems construct answers about brands and business topics alike.

The travel and retail traffic figures Semrush cited in the June 26 release also build on a trend Adobe has tracked publicly for well over a year. Adobe reported a 1,100% year-over-year increase in AI traffic to United States retail sites when it launched its LLM Optimizer product in October 2025, a figure PPC Land documented at the time. The newer 1,324% figure covering the longer October 2024 through May 2026 window suggests the underlying growth rate has not slowed materially since that earlier disclosure, even as the AI search category itself has matured and diversified across additional platforms.

Why this matters for marketers

For paid search and organic search practitioners, the report's central statistic, the 81% versus 36% gap between integrated and siloed AI-SEO strategies, offers one of the few quantified arguments available for restructuring how marketing teams are organized around AI visibility work. Many organizations built SEO teams, content teams, and public relations functions as separate reporting lines long before AI-generated answers became a meaningful discovery channel. The Semrush data suggests that separation now carries a measurable performance cost, though the survey does not establish which specific organizational changes, shared reporting structures, unified tooling, or cross-functional governance, drive the difference most directly.

PPC Land's coverage of the broader AI visibility measurement landscape has documented a recurring theme across multiple vendors and research efforts throughout 2025 and 2026: brands consistently underestimate how much of their AI-era visibility depends on sources they do not directly control. A separate Similarweb study, detailed by PPC Land, found that AI-recommended brands were 2.5 times more likely to receive a website visit within seven days of a recommendation, even though standard analytics tools capture almost none of the interaction that led to that visit. The measurement problem Semrush describes and the traffic-attribution problem Similarweb describes are, in effect, two views of the same underlying shift: AI systems now mediate a meaningful share of brand discovery through a pathway that produces almost no data trail until well after the influence has already occurred.

For publishers and content platforms specifically, the concentration data by industry vertical carries its own implications. Categories such as Finance and Industrial, where the top three brands account for less than half of total category visibility, may represent areas where independent and niche publishers retain more influence over AI citation patterns than in categories such as News and Media, where three dominant brands already claim over 80% of the visibility Semrush measured. That distinction matters for advertisers deciding where to invest in earned media or content partnerships intended to build AI-era discoverability rather than conventional search rankings alone.

Timeline

  • September 2025: Semrush launches the original AI Visibility Index, based on an initial sample of 2,500 prompts.
  • October 2025: Semrush discloses tripling its own AI share of voice from 13% to 32% in one month after finding ChatGPT recommended competitors but not Semrush itself.
  • October 14, 2025: Adobe launches LLM Optimizer, citing a 1,100% year-over-year increase in AI traffic to United States retail sites.
  • November 19, 2025: Adobe announces its $1.9 billion acquisition of Semrush.
  • January through April 2026: Semrush collects the 126 million United States AI search prompts underlying the expanded index.
  • June 9, 2026: Semrush publishes separate research on 89,000 LinkedIn URLs cited across AI search platforms.
  • June 26, 2026: Semrush publishes the expanded 2026 AI Visibility Index, based on the full 126 million-prompt dataset.

Summary

Who: Semrush, the search and generative engine optimization platform operating under Adobe ownership since November 2025, published the research. Rachel Thornton, chief marketing officer of Adobe Enterprise, and Andrew Warden, vice president of marketing at Adobe and former chief marketing officer of Semrush, provided commentary included in the announcement.

What: Semrush released the expanded 2026 AI Visibility Index, analyzing 126 million United States AI search prompts collected between January and April 2026 across ChatGPT, Google Gemini, Google AI Mode, and Google AI Overviews. A companion marketer survey found that 81% of organizations integrating SEO and AI visibility into a single workflow reported increased AI-platform traffic or leads, compared with 36% among organizations managing the two separately. Adobe traffic data cited in the same release showed AI-referred traffic to United States retail sites up 1,324% and to travel sites up 2,215% between October 2024 and May 2026, while 45% of surveyed marketing leaders said they cannot accurately measure their own brand's AI visibility.

When: Semrush published the index on June 26, 2026. The underlying prompt data was collected from January through April 2026.

Where: The prompt dataset covers United States AI search activity specifically. The report and its accompanying tools are available through Semrush's website and Adobe's business site.

Why: The findings matter because they attach a quantified performance gap to a structural choice many marketing organizations have not yet revisited: whether SEO, content, and AI-visibility functions operate as one coordinated discipline or as separate reporting lines. With AI-referred traffic climbing by multiples in categories such as travel and retail, and with fewer than one in ten marketing leaders able to track every relevant AI-visibility metric, the report frames integration less as a best practice and more as a measurable driver of whether a brand's investment in AI-era discovery actually converts into traffic.