Is SEO outdated? Semrush presents a new framework to measure brand visibility

Companies are thus encouraged to rethink their organization by:

• Creating smooth bridges between SEO, content marketing, and data science teams
• Establishing cross-functional governance to harmonize indicators and tools
• Training employees in new skills related to agentic optimization
• Deploying unified dashboards for a centralized visibility view

This organizational change is essential to fully leverage emerging technologies and master KPIs sometimes complex to interpret in a context where users no longer “visit” websites but consume information differently.

Regulatory Developments and Implications for Digital Marketing

The transformation of online visibility does not take place solely in a technical or commercial framework; it also occurs within a regulatory context in full evolution. The European Commission, through the Digital Markets Act (DMA), is establishing new standards aimed at regulating actors controlling search and AI environments.

These initial conclusions now consider that chatbots integrating search functions must be treated like traditional search engines. This qualification thus brings conversational AI environments closer to regulated models, which can significantly influence marketing practices.

For marketers, this results in several consequences:

• Clarification of data access rules: Platforms will possibly need to ensure greater transparency concerning their algorithms’ functioning and the way answers are generated.
• Increased pressure on data protection: Interactions via AI often involve personal information, raising issues related to confidentiality and consent.
• Modification of SEO/AI strategies: Regulatory evolution will likely encourage fairer competition and the possibility of better traceability of visibility opportunities.
• Strengthening of brand responsibility: They will need to ensure that their content complies with ethical standards, notably regarding misinformation and data usage.

Ultimately, digital marketing transformations looking toward 2026 will have to integrate within this evolving regulatory framework. The ability to adapt and anticipate will become a key success factor in managing brand visibility.

Essential Semrush Tools to Manage Multi-Channel and AI Visibility

Faced with the growing complexity of digital ecosystems, Semrush offers a range of integrated tools to measure and improve brand visibility on several fronts. These solutions cover natural referencing, paid advertising, social networks, but now also visibility on AI platforms.

Among the major features are:

• SEO Toolkit: In-depth SEO analysis with technical audits, position tracking, and competitive benchmarking.
• AI Visibility Index: Tracking brand mentions and share of voice in answers generated by AI agents such as ChatGPT or Google AI Mode.
• Content Automation: Assistance with creating optimized content adapted to multiple conversational formats.
• Unified Reporting: Dashboard combining classic SEO data and performance in AI environments for a 360° view.
• PPC and Social Media Analysis: Measurement of paid campaigns and social visibility for effective and targeted budget management.

This toolset provides a solid foundation for marketing professionals to structure an omnichannel strategy integrating the complexity of the current digital landscape. Performance now relies on the capacity to simultaneously optimize presence on classic engines and in AI universes.

Semrush Tool	Description	Added Value
SEO Toolkit	SEO audit, keyword tracking, technical analysis	Optimization of traditional organic rankings
AI Visibility Index	Tracking brand mentions on AI platforms	Measurement of visibility in conversational AI answers
Content Automation	AI-assisted writing adapted to conversational queries	Time savings and optimized content quality
Unified Reporting	Dashboards combining SEO and AI	Global and coherent performance view
PPC & Social Media Analysis	Measurement of advertising campaigns and social visibility	Better budget allocation and precise targeting

At a time when search engines are evolving and artificial interfaces are taking on an increasingly prominent role, brand visibility is undergoing a profound transformation. Natural referencing (SEO), long the essential foundation of digital strategy, is slowly giving way to the rise of responses generated by artificial intelligence. This phenomenon disrupts the rules of digital marketing: internet users click less and less on traditional links and prefer to consult directly the summaries offered by conversational agents. Faced with this major change, Semrush unveils a new methodology called the “Brand Visibility Framework.” This innovative framework proposes to assess the real presence of brands, not only in classic results but also in ecosystems driven by artificial intelligence. As the digital landscape becomes a multipolar universe blending traditional SEO and agent-based search, better understanding and measuring this visibility now stands as a major strategic challenge.

This revolution in visibility measurement responds to striking data: organic click-through rates have dropped by up to 61% when AI previews appear in search results. Moreover, 62% of brands remain invisible in these generative AI environments. The boundary between classic referencing and presence in AI responses is therefore becoming blurred, and the way brands position themselves must adapt. 2026 thus marks a turning point in digital analysis with Semrush at the forefront of the change to equip marketers with tools and indicators to tackle these new challenges.

Why Traditional SEO Is No Longer Enough to Ensure Brand Visibility

For more than twenty years, natural referencing has been the indispensable compass for brands seeking visibility on the web. The principle was simple: optimize the positioning of a website on search engines to attract targeted traffic. This logic was based on the structure of search results, organized in lists of links where each gained position represented an additional opportunity. However, this classic scheme no longer responds to current evolutions in user behavior and underlying technologies.

Search engines have initiated a transition toward interfaces centered on answers synthesized by artificial intelligence. In this context, clicks on links decrease. Between May 2024 and May 2025, the share of no-click searches increased from 56% to 69%. Today, nearly half of the queries display AI previews, and in certain sectors, this figure climbs up to 80% for informational queries. This means that internet users often get their answer without leaving the search page.

This transformation complicates the mission of brands, which must now not only aim for good traditional SEO rankings but also be included in the answers generated by AI. Moreover, inclusion logics change completely. Language models no longer just rank pages but compose answers by combining their training data, real-time information, and internal reasoning.

To illustrate this new reality, we can mention certain AI platforms such as ChatGPT, which today claim 800 million weekly users, or Perplexity, which processes hundreds of millions of queries per month. Their engines now influence how internet users search for and consume information. Their traffic generates an average conversion rate of 14.2%, which far surpasses the 2.8% of traditional search. This level of performance demonstrates the enormous strategic interest in standing out in these environments.

Brands thus face a formidable challenge: adapting to visibility fragmented between SEO referencing and inclusion in AI answers. SEO, even optimized, is no longer the ultimate goal but the foundation of a broader strategy, incorporating agentic and conversational search. This evolution impacts priorities, tactics, and tools used to monitor presence on the web.

The Semrush Brand Visibility Framework: A New Approach to Assess Digital Visibility

Faced with the increasing complexity of search environments, Semrush introduces an innovative framework called the “Brand Visibility Framework.” Designed to go beyond the unidimensional vision of SEO, this model takes into account brand presence in classic results but especially in answers driven by artificial intelligence and conversational agents.

This framework relies on massive analysis: over 213 million queries from large language models are examined to understand how a brand is mentioned, recognized, or overlooked in a no-click universe. Unlike classic referencing, which focuses on page ranking and generated traffic volume, brand visibility according to Semrush is measured by the capacity to be discoverable, credible, and commercially activatable on any search channel, human or automated.

This methodology proves essential because the criteria used by AI models to construct their answers are not limited to an SEO positioning but also mobilize authority signals, data structuring, and semantic quality of the content. For example, content well ranked on Google may be ignored by AI if it is not formulated in a suitable structure or is not identified as relevant for a given query.

The Brand Visibility Framework notably includes:

• Analysis of brand mentions on platforms like ChatGPT, Perplexity, and Google AI Mode
• Evaluation of brands’ share of voice in AI answers
• Measurement of conversion capability in a universe where click becomes less systematic
• Consideration of evolving user habits and expectations

Through this new approach, Semrush places referencing within a broader set, where visibility no longer rhymes only with positioning in classic engines but extends to direct recognition by artificial intelligences that now orchestrate a significant share of online interactions.

How Optimization for Agentic Search Revolutionizes Brand Visibility

At the core of the new Semrush model, optimization for agentic search constitutes a true conceptual and strategic revolution. This discipline emerges to answer a new actor in the information chain: AI agents, which produce synthetic responses from vast data.

Traditionally, SEO addressed human users who scanned a list of results on Google or Bing. Optimization thus aimed to maximize ranking and encourage clicks. This paradigm completely changes with the rise of conversational agents. These seek to provide a single direct answer, often without offering a link to consult. Referencing thus becomes an exercise in algorithmic influence where the goal is to appear in the formulation of the answer, not just in the list of results.

For illustration, Semrush highlights a striking statistic: only between 8% and 12% of content featured in AI answers corresponds to pages in the first position on Google. This finding highlights a clear gap between classic SEO and real visibility in these new environments. Being number one on a keyword does not guarantee visibility in answers generated by artificial intelligence.

Agentic optimization thus requires to:

1. Understand the selection criteria used by language models and conversational agents
2. Produce structured content, exploitable by AI, with clear markup and enriched data
3. Develop real digital authority through strong signals that inspire trust and credibility to AI systems
4. Adapt marketing campaigns to conversational and multi-channel formats

This new optimization aspect is accompanied by innovative tools such as Semrush’s AI Visibility Index. This tracks brand mentions in AI environments, providing marketers with a parallel to traditional SEO keywords in conversational mode.

The rise of this discipline forces companies to reconsider their strategies to avoid losing ground in a deeply changed digital landscape.

The Concrete Impacts of Declining Organic Clicks on Marketing Performance

The drop in organic clicks directly impacts buying behaviors and marketing campaign performance. Indeed, recent data show that the appearance of AI previews in results can reduce clicks by up to 61%. A significant impact for brands relying on this traffic source to feed their conversion funnel.

This phenomenon combines several factors. On the one hand, search engines provide complete and instant answers. On the other hand, navigation control becomes more complex: users no longer move to third-party sites to find their information. For marketers, this requires rethinking how to capture attention and convert directly within the AI sphere.

But paradoxically, AI search presents better traffic quality. The user conversion rate reaches 14.2% in these environments, five times higher than traffic from traditional SEO (2.8%). This figure illustrates another reality: the volume of queries originating from AI is more limited, but its commercial impact is significant.

Brands that can combine classic SEO optimizations with performance in agentic search will benefit from a significant competitive advantage, their marketing resources being better allocated and generating a better return on investment.

To optimize this performance, it is now necessary to:

• Track share of voice in AI environments in real time
• Integrate artificial intelligence into content creation and distribution
• Combine natural referencing and presence in conversational agents
• Measure impact on the customer journey from discovery to purchase

Adobe’s Acquisition and Its Impact on the Future of Digital Visibility

This year is marked by a major event in digital marketing: the acquisition of Semrush by Adobe, a deal valued at 1.9 billion dollars. This buyout highlights the growing importance of platforms combining SEO, AI visibility, and advanced analytics to drive marketing strategies.

This strategic alliance brings together two giants, Adobe contributing its expertise in digital content creation and massive data management, while Semrush brings its powerful SEO analysis and multi-channel visibility tools. The duo thus opens the way to seamless integration between presence measurement on classic engines and new AI systems.

In practice, this synergy will allow brands access to:

Feature	Impact	Benefit for Brands
Combined SEO/AI measurement	Holistic visibility vision	More effective multi-channel optimization
AI-assisted content creation	Fast and targeted content production	Time savings and increased relevance
Predictive trend analysis	Anticipation of market changes	Enhanced strategic responsiveness
SEO task automation	Error and cost reduction	Better resource allocation

The challenge goes beyond simple analysis; it involves supporting a future where visibility and performance intertwine in a permanent hybrid universe between humans and artificial intelligences. The acquisition consolidates Semrush’s position at the heart of digital marketing strategies for the decade.

How to Organize Marketing Teams to Track the New Visibility of Brands

Adapting to new forms of visibility induced by AI concerns not only technology but also requires deep organizational evolution. Semrush’s Brand Visibility Framework highlights a key finding: teams that align SEO, content creation, and AI strategy obtain significantly better results.

This coordination fosters effective management, allowing tracking of emerging indicators related to agentic search, AI answer visibility, and direct conversion in a no-click environment. Conversely, functional silos or barriers between SEO and AI slow down data exploitation and limit performance.

Companies are thus encouraged to rethink their organization by:

• Creating smooth bridges between SEO, content marketing, and data science teams
• Establishing cross-functional governance to harmonize indicators and tools
• Training employees in new skills related to agentic optimization
• Deploying unified dashboards for a centralized visibility view

This organizational change is essential to fully leverage emerging technologies and master KPIs sometimes complex to interpret in a context where users no longer “visit” websites but consume information differently.

Regulatory Developments and Implications for Digital Marketing

The transformation of online visibility does not take place solely in a technical or commercial framework; it also occurs within a regulatory context in full evolution. The European Commission, through the Digital Markets Act (DMA), is establishing new standards aimed at regulating actors controlling search and AI environments.

These initial conclusions now consider that chatbots integrating search functions must be treated like traditional search engines. This qualification thus brings conversational AI environments closer to regulated models, which can significantly influence marketing practices.

For marketers, this results in several consequences:

• Clarification of data access rules: Platforms will possibly need to ensure greater transparency concerning their algorithms’ functioning and the way answers are generated.
• Increased pressure on data protection: Interactions via AI often involve personal information, raising issues related to confidentiality and consent.
• Modification of SEO/AI strategies: Regulatory evolution will likely encourage fairer competition and the possibility of better traceability of visibility opportunities.
• Strengthening of brand responsibility: They will need to ensure that their content complies with ethical standards, notably regarding misinformation and data usage.

Ultimately, digital marketing transformations looking toward 2026 will have to integrate within this evolving regulatory framework. The ability to adapt and anticipate will become a key success factor in managing brand visibility.

Essential Semrush Tools to Manage Multi-Channel and AI Visibility

Faced with the growing complexity of digital ecosystems, Semrush offers a range of integrated tools to measure and improve brand visibility on several fronts. These solutions cover natural referencing, paid advertising, social networks, but now also visibility on AI platforms.

Among the major features are:

• SEO Toolkit: In-depth SEO analysis with technical audits, position tracking, and competitive benchmarking.
• AI Visibility Index: Tracking brand mentions and share of voice in answers generated by AI agents such as ChatGPT or Google AI Mode.
• Content Automation: Assistance with creating optimized content adapted to multiple conversational formats.
• Unified Reporting: Dashboard combining classic SEO data and performance in AI environments for a 360° view.
• PPC and Social Media Analysis: Measurement of paid campaigns and social visibility for effective and targeted budget management.

This toolset provides a solid foundation for marketing professionals to structure an omnichannel strategy integrating the complexity of the current digital landscape. Performance now relies on the capacity to simultaneously optimize presence on classic engines and in AI universes.

Semrush Tool	Description	Added Value
SEO Toolkit	SEO audit, keyword tracking, technical analysis	Optimization of traditional organic rankings
AI Visibility Index	Tracking brand mentions on AI platforms	Measurement of visibility in conversational AI answers
Content Automation	AI-assisted writing adapted to conversational queries	Time savings and optimized content quality
Unified Reporting	Dashboards combining SEO and AI	Global and coherent performance view
PPC & Social Media Analysis	Measurement of advertising campaigns and social visibility	Better budget allocation and precise targeting