Summary: Semrush launched a Brand Visibility Framework at Adobe Summit introducing “Agentic Search Optimisation” as a new discipline for measuring brand presence across AI-generated answers, traditional search, and autonomous AI agents, drawing on 213 million LLM prompts. The framework arrives as organic click-through rates have dropped 61% on queries with AI Overviews, 62% of brands are invisible to generative AI, and Semrush’s own AI product revenue has grown 850% to $38 million ARR, all while the company awaits completion of its $1.9 billion acquisition by Adobe.
Semrush used its slot at Adobe Summit in Las Vegas to launch what it calls a Brand Visibility Framework, a strategic model for measuring how brands are discovered across traditional search engines, AI-generated answers, and autonomous AI agents. The framework introduces “Agentic Search Optimisation” as a new operational discipline and draws on a database of more than 213 million large language model prompts to show brands exactly how they are being discussed, recommended, or ignored inside systems where no human ever clicks a link.
The timing is not coincidental. Semrush is in the process of being acquired by Adobe for $1.9 billion, a deal announced in November 2025 and expected to close in the first half of this year. The framework positions Semrush’s capabilities as the visibility layer within Adobe’s marketing stack at a moment when the question of where brands appear is being fundamentally rewritten by AI.
The problem the framework addresses
The data behind the framework is bleak for anyone whose business depends on organic search traffic. Gartner predicted in February 2024 that traditional search engine volume would drop 25% by 2026 due to AI chatbots and virtual agents. The prediction is tracking. Google’s AI Overviews now trigger on 48% of all tracked search queries, a 58% increase year over year, and on 80 to 88% of informational queries depending on the industry. Organic click-through rates have plummeted 61% for queries where AI Overviews appear, according to Seer Interactive. Paid search click-through rates crashed from roughly 11% to 3% in a single month last year.
Zero-click searches, where a user gets an answer without visiting any website, increased from 56% to 69% of all queries between May 2024 and May 2025. ChatGPT now has 800 million weekly active users. Perplexity processed 780 million queries in May 2025 alone. The traffic that does arrive from AI search converts at 14.2%, compared with 2.8% from traditional Google search, but there is dramatically less of it, and brands have almost no control over whether an AI system mentions them at all.
The most striking finding in the research accompanying the framework is the disconnect between investment and visibility. While 94% of brands invest heavily in traditional SEO, 62% are what Semrush calls “technically invisible” to generative AI models. Only 8 to 12% overlap exists between the results that appear in AI-generated answers and those that rank well in traditional search. ChatGPT Search primarily cites pages ranked 21st or lower, meaning the entire edifice of search engine optimisation, the industry Semrush built its business on, does not reliably translate into visibility in the systems that are replacing it.
What the framework proposes
Semrush defines brand visibility as “the degree to which a brand is discoverable, authoritatively represented, and commercially actionable across both human- and machine-mediated discovery surfaces.” The framework arrives as a two-part research series: one covering execution of what it calls a Brand Visibility Operating Model, the other offering a strategic overview for chief marketing officers navigating AI search.
The operational centrepiece is Agentic Search Optimisation, which Semrush distinguishes from traditional SEO. Where search engine optimisation was built for a world in which a human scanned a list of links and chose one, Agentic Search Optimisation is built for a world in which an AI agent evaluates brand relevance and authority on behalf of the user, then surfaces a recommendation without presenting alternatives. The distinction matters because the mechanics are different. AI systems do not rank pages. They synthesise answers from training data, real-time retrieval, and internal reasoning, and the factors that determine whether a brand is included in that synthesis are not the same factors that determine whether it ranks on page one of Google.
The framework builds on Semrush’s AI Visibility Index, launched in October 2025, which tracks brand mentions, mention position, website citations, and share of voice across ChatGPT, Google AI Mode, Perplexity, and Gemini. The index draws on the 213 million LLM prompt database to function as what Semrush describes as “keyword research for AI,” mapping the topics, intent, and volume of queries that users direct at AI systems rather than search engines.
The commercial context
Semrush reported $443.6 million in revenue for fiscal 2025, up 18% year over year, with annual recurring revenue reaching $471.4 million. The company has 117,000 paying customers and more than 10 million total users. But the most telling number is the growth of its AI products: annualised recurring revenue from AI-specific tools surpassed $38 million, up from $4 million the prior year, representing roughly 850% growth. Customers paying more than $50,000 annually grew 74%.
The Adobe acquisition, at $12 per share in an all-cash deal, values Semrush at approximately $1.9 billion. German competition authorities cleared the deal unconditionally in March. UK CMA proceedings are ongoing. The strategic logic is straightforward: Adobe’s marketing cloud has tools for creating and delivering content but lacks a comprehensive layer for understanding where that content is discovered. Semrush provides that layer, and the Brand Visibility Framework effectively serves as the intellectual architecture for how it will fit into Adobe’s product line.
Bill Wagner, who became Semrush’s CEO in March 2025 when co-founder Oleg Shchegolev moved to chief technology officer, framed the shift explicitly. “Search Engine Optimisation continues to be table stakes,” he said, “but marketers now need new tools to navigate the always-changing AI visibility equation.” The company completed a brand identity refresh in March, repositioning itself from an SEO toolkit to what it calls a “brand visibility platform built for the age of AI-driven discovery.”
What it means for the industry
Semrush is not alone in recognising the shift. Ahrefs has added AI Overviews tracking to its Keywords Explorer. Moz Pro launched an AI Visibility feature in open beta. Startups like Lemrock are building commerce layers specifically for AI agents, connecting retailers to ChatGPT, Claude, and Perplexity through a single integration. Some retailers are already reporting traffic declines of up to 30% as consumers shift queries from Google to AI systems.
The framework’s key research finding underscores why this matters organisationally, not just technically. Among teams that are fully aligned on search and AI optimisation, 55% said brand visibility is “clearly measurable and actionable.” Among partially aligned teams, that figure drops to 15.5%. Siloed teams, where SEO, content, and AI strategy are managed separately, reported AI visibility as “very difficult to measure” at a rate of 24.6%. The implication is that the problem is not primarily technological but structural: most marketing organisations are not set up to manage visibility across systems that work fundamentally differently from each other.
The European Commission’s recent preliminary findings under the Digital Markets Act explicitly classified AI chatbots with search functionalities alongside traditional search engines, a regulatory signal that the distinction between “search” and “AI answer” is collapsing in policy as well as practice. For brands, the question is no longer whether AI search will change how they are discovered. It is whether they will be discovered at all.
Semrush’s framework does not answer that question definitively, but it does something that most of the industry’s responses to AI search have not: it names the problem precisely, provides a measurement system for tracking it, and offers an organisational model for addressing it. Whether that model survives contact with the reality of how AI systems actually select and surface brands will determine whether the Brand Visibility Framework becomes a genuine strategic standard or an elaborate product launch dressed in the language of thought leadership.
