Semrush unveils Agentic Search Optimisation as AI search rewrites brand visibility rules

Semrush Brand Visibility Framework launches at Adobe Summit as AI search rewrites discovery rules

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 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. 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. 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." 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.

Agentic Search Optimization reshapes brand visibility in AI search

Search is evolving fast, brands must adopt ASO to stay visible in AI-driven discovery For the last 18 months, AI has fundamentally disrupted the way people search and find information. The SEO industry's response was disjointed, and -- let's be honest -- entirely reactive. We simply did not have the data to understand what was changing, how fast it was changing, and where we would ultimately end up. Back then, rather than solving for the actual problem, such as lost traffic, broken attribution, and the looming threat to revenue, practitioners reached for a lexicon. We saw a sudden explosion of new acronyms: GEO, AEO, LLMO. Each new acronym narrowed the conversation to a single tactic. Each one splintered budgets and reinforced a categorically incorrect idea: in order for brands to be visible in the AI era, radically different approaches needed to be built from scratch. It's been a distraction. While the industry is busy debating acronyms, the actual behavior of the consumer -- and the search surfaces -- are evolving right in front of us. The end of the acronym soup The dust has finally settled. And I want to remind everyone of something that should make marketers breathe a sigh of relief: the core human behavior behind search, including curiosity, problem-solving, decision-making, hasn't changed. Just as importantly, brand visibility in the AI era is still built on the same foundations that have always driven great SEO: crawlable infrastructure, authoritative content, and consistent brand signals. But SEO alone is no longer enough. Today AI search systems are constructing answers rather than simply ranking links. They retrieve, evaluate, and synthesize information across multiple inputs, then surface recommendations, often without sending users to a website at all. The intermediary has changed. And with it, the entire surface area that determines whether your brand gets selected. This shift is already visible in the data. AI Overviews appear on roughly 16% of Google search results, and generative platforms like ChatGPT, Perplexity, and Claude are increasingly becoming part of everyday research behavior. The latest research shows also that AI-driven search traffic grew from under 2% to more than 9% of desktop search traffic between 2024 and 2025, while traditional Google searches per user in the U.S. declined by nearly 20% during the same period. The implication is clear: visibility today is about being selected based on the strength, consistency, and authority of your entire digital presence. This is why the conversation needs to move beyond acronym dissonance and name the shift for what it actually is now and will likely be into the future: a new operating layer for discovery. This shift is called Agentic Search Optimization (ASO). Why ASO? Every AI-generated answer already involves a machine retrieving sources, judging credibility, and composing a response. That's agentic behavior, and it's happening today in ChatGPT, Google AI Mode, and Perplexity. What's emerging now are agents that browse, compare, and transact with no human in the loop. ASO is the discipline that ensures your brand is found, understood, and trusted across that entire spectrum. Every time an AI system processes your brand, compares it to others, and determines whether to include it in a response, that is an agentic decision. And those decisions are not based solely on your website; AI agents interpret the entire digital footprint, including media coverage, Reddit discussions, YouTube videos, reviews, partner mentions. And here's the shift most brands are still underestimating: AI doesn't just want to hear from you. It wants to hear what others are saying about you. That's why, in my view, Agentic Search Optimization, combined with core SEO principles, represents both the present and the future of brand visibility. Why search is now a board-level concern For too long, SEO was treated as a marketing motion and, in many cases, an individual contributor's task. Those days are over. In an AI-driven environment, visibility is not created through isolated efforts. It's the result of how consistently your brand shows up across every surface that influences discovery. That makes search a reflection of the entire business. Which is why it now sits at the board level. Growing visibility today requires synchronized alignment across content, brand, product, and communications to create consistent, AI-trusted signals at every touchpoint. Because when visibility depends on consistency, misalignment becomes a growth risk. If your content says one thing, your product signals another, and your external presence tells a different story, AI systems don't reconcile that in your favor. Instead, they dilute it, and that dilution has a cost. This is what I call "The Beige Tax", the cost of safe, generic, average content. In an AI-driven environment, mediocre doesn't just underperform-it disappears. The only way to compete is through signal alignment: ensuring that every part of your organization reinforces the same narrative, with enough authority and consistency for AI systems to trust and surface it. Winning in the next era The biggest misconception about this shift is that it requires starting over. It doesn't. Winning in this era is accretive meaning it builds on what already works. Once again, the same fundamentals apply. But they need to scale across more surfaces, more signals, and more systems. From our data, three factors consistently drive AI visibility: Entity authority: If people aren't searching for your brand, AI won't either. Brand demand is now a leading indicator of inclusion. Information density and originality: AI prioritizes content that adds something new -- proprietary data, unique insights, strong perspective. Original research can increase visibility by 30-40%. Signal alignment: Consistency across channels matters more than ever, because AI looks for consensus across your ecosystem rather than simply trusting isolated claims. This is how brands move from being indexed... to being selected. The future is clearer, but it doesn't mean it's easier The future of brand visibility demands the combination of SEO + ASO. We aren't asking teams to start from scratch; we are making the case that investment in teams, tools, and strategy must expand to match the new surfaces that influence search. There are plenty of "AI-native" point solutions popping up right now. They can track a mention or see a single moment in a ChatGPT window. But they lack the historical depth and competitive benchmarking required to contextualize why performance is shifting. They see a moment. At Semrush, we see the trajectory. The goal for any brand today is simple but difficult: build durable visibility wherever people search. AI just made "being everywhere" the most valuable place to be. The brands that win in the next era will be the ones that show up consistently across exactly there -- everywhere. The shift is here, and the data is clear.