The paradigm shift: from classic SEO to generative SEO

The evolution of search engines and the rise of generative Artificial Intelligence are completely redefining the concept of SEO. It’s no longer just about optimizing for Google, but also about understanding how content interacts with models like ChatGPT, Claude, Gemini, or generative search engines like Perplexity.

This transformation involves a leap from the classic keyword approach to a strategy focused on being a source of reliable and relevant information to train and feed these new systems.

What are GEO, AIO and LLMO and why you should integrate them?

GEO (Generative Engine Optimization) focuses on creating content that is not only indexed but also cited by AI-based answer engines. AIO (Artificial Intelligence Optimization) seeks to understand how AI algorithms select sources for their answers. LLMO (Large Language Model Optimization) delves even deeper, focusing on directly influencing the training of language models.

Adopting these frameworks allows you to design content that transcends traditional SEO: texts designed to be read, understood, and referenced by models.

New engines, new rules: the battle for visibility

Platforms like Perplexity or the integration of generative AI into Bing and Google (AI Mode) are changing the way users interact with information. Instead of displaying a list of links, these engines generate comprehensive and detailed answers based on previously published content. Therefore, being a reliable and cited source becomes key.

Visibility is no longer just a matter of ranking in the top 10 results, but rather a matter of semantic influence.

Content that cites and ranks: the importance of being a source

If the model doesn’t mention you, you don’t exist. This phrase sums up the new dynamics of positioning. It’s not enough to be relevant to the reader: now you have to be useful to the models too. Content must answer questions, offer accurate data, demonstrate authority, and be semantically well-structured.

Strategies such as using tables, lists, structured data, and clear, topic-focused writing help LLMs identify these as valuable and integrate them into their responses.

What do models look for? How do they train response generators?

Language models are trained on large corpora of text: blogs, news, forums, academic articles. They identify patterns of coherence, authority, currency, tone, and structure. Therefore, creating content with a natural yet technical approach, reliable yet relatable, up-to-date, and unique is essential in the new AI-powered SEO.

The more cited content, the greater the chance of appearing in the response generation. Invisible or generic content will be left out of the game.

User experience and prompts: SXO’s new tandem

SXO (Search Experience Optimization) takes on a new life in this context. It’s not just about UX and dwell time, but about understanding what types of prompts generate appearances in generative search engines and adapting the content structure to respond to those prompts.

For example, if people ask “what’s the difference between SEO and GEO?”, having a clear section with that explanation increases your chances of being cited. Content design is no longer just visual or technical: it must also be prompt-friendly.

How to adapt your content strategy in 2025

  1. Research real questions: Analyze platforms like Answer the Public, Perplexity, or Reddit to identify real concerns.
  2. Be useful and specific: General content has less impact on AI. The more specific, the better.
  3. Create for humans and models: clarity, structure, semantics. Avoid filler. Strive for depth.
  4. Update frequently: Models prefer fresh, authored content.
  5. Consolidate authority: mentions on other websites, links, social media activity.

Positioning is transformed, but its essence remains

As consultant Iñaki Huerta says: “Ultimately, it’s all about SEO.” This phrase, which may seem like an oversimplification, contains a profound truth: the discipline of positioning has transformed, but its essence remains the same.

What remains true is the need to showcase ourselves, to be visible and found when there’s demand for our products or services. Whether it’s a generative model, a search engine, or a social media algorithm, the goal is the same: to occupy a place in the user’s mind with our brand. And that will continue to be the responsibility of SEO professionals, who must adapt to the new rules of the game to stay relevant.

SEO in 2025 isn’t dead, nor is it broken: it’s evolved. The tools change, the environments too, but the goal remains the same: to be discovered, to be useful, to be relevant.

Adopting new strategies like GEO, AIO, and LLMO, understanding generative models, and optimizing for them is no longer optional or a competitive advantage; it’s the new standard.

If you already have a solid SEO foundation, implementing GEO requires a shift in approach. Instead of focusing solely on rankings, start creating content that addresses specific questions, has a clear structure, accurate data, and is designed to be cited. GEO is about being a source of answers, not just visibility.

LLMs prefer well-structured content with clear explanations, up-to-date data, and proven authority. Lists, comparison tables, FAQ sections, and texts focused on a specific topic increase the likelihood of being used as a source by generative models.

Platforms like Perplexity, Answer the Public, or AlsoAsked allow you to discover how users ask questions. With them, you can identify topics and formats that the models use as reference. It’s also useful to use GPTs or generative AI to test how users interpret and respond to your content.

One of the most common mistakes is forcing keywords without considering the semantic context. So is creating superficial or overly generic content. Another common mistake is ignoring structure: without clarity, LLMs can’t properly interpret the content’s value. Also, avoid unnecessary padding.

Perplexity highly values ​​accurate, well-contextualized answers with verifiable sources. A good structure includes clear headings (H2, H3), numbered lists, definitions, FAQ sections, and links to reliable sources. Clarity is key to being cited.

Models value content with clear authorship because they associate authority and trustworthiness with the author. Including your name, experience, and links to your professional profile or external publications can increase the credibility of the text and its likelihood of being integrated into generated responses.

Yes, because being cited by generative models right now is like being well-positioned before a keyword explodes. You gain authority, increase your future visibility, and build a long-term competitive advantage. Generative engines are growing, and it’s only a matter of time before they dominate.

Sectors with a high volume of specific queries, such as healthcare, finance, technology, law, and education, are already seeing results. B2B niches with technical or specialized content also have advantages, as LLMs prioritize in-depth, reliable, and highly informative texts.

Emiliano Harri Echeverría
Consultor SEO at  • harri@smart-team.io

Consultor de Marketing y SEO con más de 10 años de experiencia en optimización web y estrategias digitales. Ayudo a negocios locales, pymes y grandes empresas a mejorar su posicionamiento online, alcanzar sus objetivos de crecimiento y adaptarse a un mundo digital cada día más competitivo.