Semrush launches framework for measuring brand visibility in AI search as old SEO playbook breaks down

At a glance:

• Semrush unveils Agentic Search Optimisation to track brand presence across AI-generated answers and traditional search.
• Framework draws on 213 million LLM prompts as organic click-through rates drop 61% where AI Overviews appear.
• Launch coincides with Adobe’s $1.9 billion acquisition of Semrush and 850% growth in AI product revenue to $38 million ARR.

The old SEO playbook is failing as AI answers replace links

At Adobe Summit in Las Vegas, Semrush unveiled its Brand Visibility Framework, positioning it as the measurement layer for an era in which AI-generated answers, not blue links, dominate discovery. The framework introduces “Agentic Search Optimisation” as a new operational discipline, built to track how brands surface inside large language models, AI Overviews, and autonomous agents that never present a clickable list. It arrives as Gartner’s 2024 prediction—that traditional search volume would fall 25% by 2026 due to AI chatbots—appears to be tracking, with Google’s AI Overviews now triggering on 48% of tracked queries, up 58% year over year.

The data underpinning the shift is stark. Organic click-through rates have plummeted 61% on queries where AI Overviews appear, while paid search click-through rates collapsed from roughly 11% to 3% in a single month last year. Zero-click searches—where users get answers without visiting any website—jumped from 56% to 69% of all queries between May 2024 and May 2025. ChatGPT now claims 800 million weekly active users, and Perplexity processed 780 million queries in May 2025 alone. 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 visibility gap: 62% of brands are invisible to generative AI

The most striking finding in Semrush’s accompanying research is the disconnect between investment and actual presence. While 94% of brands invest heavily in traditional SEO, 62% are what Semrush calls “technically invisible” to generative AI models. Only 8 to 12% of results overlap between AI-generated answers and traditional search rankings. 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.

To address this, Semrush defined 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 builds on the company’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 a database of more than 213 million LLM prompts 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.

Agentic Search Optimisation: a new discipline for a new discovery layer

Where traditional SEO 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 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 the Agentic Search Optimisation discipline, which Semrush distinguishes from traditional SEO. It is designed to give marketers a systematic way to measure and influence their presence inside AI systems that increasingly mediate discovery.

Commercial context: Adobe deal and explosive AI revenue growth

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.”

Industry response: competitors and startups race to fill the gap

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.