# Adobe Launches Brand Visibility Tool for AI Search > Source: > Published: 2026-06-17 14:54:01.554192+00:00 # Adobe Launches Brand Visibility Tool for AI Search Adobe on June 17 announced **Adobe Brand Visibility**, a product that pairs Semrush AI data with Adobe content tools to help brands monitor and improve their presence inside AI-generated results, according to CMSWire. The offering provides prompt-level visibility across major generative platforms including **ChatGPT**, **Copilot**, **Perplexity**, and **Google AI Mode**, per CMSWire. Separately, Semrush introduced a **Brand Visibility Framework** at Adobe Summit that it says draws on a database of more than **213 million** LLM prompts and coins the term "Agentic Search Optimisation," according to The Next Web. The Next Web reports related market signals: organic click-through rates have fallen where AI Overviews appear, **62%** of brands are invisible to generative AI, and Semrush's AI product revenue rose **850%** to **$38 million ARR**. Industry context: marketers face rising zero-click answers and need new measurement for AI-driven discovery. ### What happened Adobe on June 17 announced **Adobe Brand Visibility**, a tool that pairs Semrush AI insights with Adobe content and optimization tooling to help businesses track mentions and presence inside AI-generated answers, according to CMSWire. CMSWire reports the product offers prompt-level visibility and competitive analysis across major generative platforms, naming **ChatGPT**, **Copilot**, **Perplexity**, and **Google AI Mode**. The Next Web reports that Semrush introduced a complementary **Brand Visibility Framework** at Adobe Summit, drawing on a database of more than **213 million** LLM prompts and describing a discipline it calls "Agentic Search Optimisation." The Next Web also reports market metrics behind the launch, including a claim that **62%** of brands are invisible to generative AI and that Semrush's AI product revenue rose **850%** to **$38 million ARR**. ### Technical details Per CMSWire, Adobe's product combines Semrush's prompt- and answer-level signals with Adobe's content tooling to surface where a brand appears in AI answers and to suggest optimization opportunities. The reporting frames the integration as giving marketers "prompt-level visibility" and comparative metrics against competitors across multiple AI platforms. The Next Web coverage characterises the framework as built on Semrush's LLM prompt dataset and positions "Agentic Search Optimisation" as a measurement model spanning traditional search results, AI-generated overviews, and autonomous agents. ### Industry context Industry observers have documented a shift toward zero-click answers as large language model overviews and agentic assistants become default interfaces for many queries. The Next Web cites external measurements showing rising trigger rates for AI Overviews and declining organic click-through rates for queries where those overviews appear. Editorial analysis: Companies and teams that depend on organic search and content discovery typically need new telemetry when endpoints move from web pages to generated answers; practitioners should therefore expect measurement and attribution demands to shift toward prompt- and answer-level signals rather than only SERP rankings. ### Context and significance Reporting places this launch at a moment of consolidation: The Next Web notes Adobe announced a pending **$1.9 billion** acquisition of Semrush in November 2025 and that the deal was expected to close in the first half of this year. For marketing and analytics teams, the combined offering collects two sets of capability: Semrush's data and framework for what the company describes as brand visibility inside LLM-driven interfaces, and Adobe's executional content toolset for optimization. Editorial analysis: For practitioners, the product and framework together represent one approach to operationalising measurement for AI-driven discovery, but they do not resolve broader attribution challenges around generated answers and multi-agent recommendations. ### What to watch Observers should track: - •independent validation or replication of the visibility metrics Semrush reports - •whether platform providers change prompt/answer metadata sharing that would affect measurement - •adoption signals from brands and agencies reporting measurable lift in traffic or conversions attributable to AI-answer optimizations. Industry context: As AI-overview coverage grows, practitioners will watch whether tools shift from ranking-centred KPIs to answer-centred KPIs and how vendors instrument that shift ## Scoring Rationale This is a notable product integration for marketing and analytics teams because it operationalises prompt- and answer-level visibility across major generative platforms. 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