{"id":821887,"date":"2026-01-27T13:14:44","date_gmt":"2026-01-27T12:14:44","guid":{"rendered":"https:\/\/www.devoteam.com\/?post_type=expert-view&p=821887"},"modified":"2026-01-28T17:48:53","modified_gmt":"2026-01-28T16:48:53","slug":"are-you-ready-for-the-new-era-of-ai-search","status":"publish","type":"expert-view","link":"https:\/\/devoteam.info\/en-pt\/expert-view\/are-you-ready-for-the-new-era-of-ai-search\/","title":{"rendered":"Are You Ready for the New Era of AI Search?"},"content":{"rendered":"\n
The Transformation in Information Retrieval<\/h2>\n\n\n\n
In recent years, information-seeking behaviour has evolved at a fast pace. The ascent of Large Language Models (LLMs) has introduced a new digital paradigm: users have moved beyond simply searching for links; they now demand direct, actionable, and conversational answers.<\/p>\n\n\n\n
In an era where traditional search engines are no longer the only starting point, the challenge for brands is clear: how can visibility and relevance be ensured in a landscape where responses are synthesised by artificial intelligence?<\/strong> In a landscape where traditional SEO is no longer sufficient, it becomes essential to adopt a new approach. This is where Generative Engine Optimisation (GEO) comes in.<\/p>\n\n\n\n
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GEO does not replace what came before, but invites us to embrace the evolution of how content is discovered, understood, and recommended.<\/em><\/p>\n\n\n\n\n\n\n\n
From Traditional Search (SEO) to Response Generation<\/h3>\n\n\n\n
The market has witnessed a significant transformation: search is no longer merely about the presentation of results, but rather the synthesis of information. We are experiencing a clear transition: from the traditional search model to an ecosystem where responses are crafted by generative models – not based on what brands say, but on what is said about them.<\/strong><\/p>\n\n\n\n<\/figure>\n\n\n\n
The surge in LLMs adoption<\/h3>\n\n\n\n
The adoption of LLM-based tools is growing exponentially. Projections suggest that by 2031, the global user base could increase by 239%<\/strong>, reflecting a fundamental shift in search habits: users now prioritise speed, conciseness, and a clear orientation towards utility.<\/p>\n\n\n\n<\/figure>\n\n\n\n
Source: Statista. (March 2025). Number of AI tool users worldwide from 2021 to 2031 (in millions).<\/p>\n\n\n\n
Whilst LLMs are gaining significant traction, traditional search engines continue to lead in traffic volume<\/strong>. In October 2025, Google exceeded 84 billion visits, accounting for approximately 86% of the total share among major engines and platforms. Bing, Yahoo, and DuckDuckGo collectively recorded roughly 5 billion visits.<\/p>\n\n\n\n
ChatGPT<\/strong>, however, registered 6.2 billion visits<\/strong> (approximately 6.3% of the total<\/strong>), clearly outperforming other generative platforms such as Gemini, Copilot, DeepSeek, and Perplexity \u2013 and even surpassing the majority of traditional search engines. Concurrently, LLM-generated traffic is growing monthly<\/strong>; according to SEMRush, it could represent 17% of total website traffic by 2026.<\/p>\n\n\n\n
These figures reinforce the need for a comprehensive, hybrid strategy<\/strong>: ensuring a presence across both traditional search engines and AI-powered platforms.<\/p>\n\n\n\n<\/figure>\n\n\n\n
LLMs synthesise responses and summaries based on specific sources. Throughout this process, many brands find themselves either omitted or misrepresented<\/strong>, simply because the models do not perceive them as relevant.<\/p>\n<\/blockquote>\n\n\n\n
Furthermore, the trend towards ‘zero-click’ searches<\/strong> is rising: in March 2025, 26.1% of searches resulted in no clicks at all (an 11% increase compared to 2024), and all indicators suggest this figure will continue to grow.<\/p>\n\n\n\n
Consequently, the objective has shifted beyond merely generating organic clicks. The focus has pivoted towards enhancing visibility, credibility, and authority<\/strong> to attract truly qualified traffic: users who purposefully choose to click because they have a genuine interest in the product or service.<\/p>\n\n\n\n
The Strategy for GEO<\/h2>\n\n\n\n
Implementing a GEO <\/strong>strategy is a structured, ongoing process, vital for securing a brand\u2019s footprint within the ecosystem of Large Language Models (LLMs) and answer engines.<\/p>\n\n\n\n
Moving beyond the traditional focus on visibility inherent in SEO, brands must now aim to educate users and guide AI response engines<\/strong> to be more efficient and accurate in the responses they share in their conversations and content.<\/p>\n\n\n\n
The process unfolds across four complementary phases:<\/p>\n\n\n\n
I. Audit and Diagnosis<\/strong><\/strong><\/h3>\n\n\n\n
A technical website analysis, digital reputation, and overall brand presence. This stage is critical for mapping the data sources<\/strong> of generative models and diagnosing how the sector and competitors are currently represented within LLMs. It concludes by identifying strengths and significant gaps in existing content.<\/p>\n\n\n\n
II. GEO Positioning Strategy <\/strong><\/strong><\/h3>\n\n\n\n
Defining the key<\/strong> topics<\/strong>, entities<\/strong>, and concepts<\/strong> that must be uniquely associated with the brand by generative models. This involves the rigorous analysis of prompts and linguistic patterns to establish a controlled narrative<\/strong> for the brand within the AI landscape.<\/p>\n\n\n\n
III. Optimisation and Implementation<\/strong><\/strong><\/h3>\n\n\n\n
This stage is dedicated to refining content based on the core criteria of clarity, authority, and relevance<\/strong> for LLMs. It includes developing long-form Q&A <\/strong>content, thematic pages, and a strategic digital PR<\/strong> and backlink acquisition plan to bolster the brand’s referential credibility.<\/p>\n\n\n\n
IV. Continuous Monitoring and Maintenance<\/strong><\/strong><\/h3>\n\n\n\n
Establishing a cycle of continuous optimisation<\/strong>, which involves regular monitoring of responses from leading models to assess the brand’s presence. This phase generates performance reports<\/strong> to adjust the strategy based on the evolution of generative models and the dynamics of user behaviour.<\/p>\n\n\n\n
GEO vs. SEO<\/strong><\/h2>\n\n\n\n
GEO does not replace SEO<\/strong>; rather, it represents its evolution. Both methodologies share a core emphasis on content quality, technical integrity, and alignment with search intent. However, the transition from search engines to answer engines<\/strong> requires that brand visibility is secured through referencing by systems built on consolidated knowledge<\/strong>. It has become imperative to ensure that AI classifies a brand as relevant, credible, and worthy of citation.<\/p>\n\n\n\n
GEO occupies a more transversal position in the definition of brand content strategy.<\/strong> It serves as an accelerator for SEO, driving a more structural and comprehensive shift.<\/p>\n\n\n\n
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