Glossary
20 clear, actionable definitions to master AEO, GEO and AI visibility terminology in 2026.
The digital marketing landscape has shifted. In 2026, over 40% of informational searches go through a generative AI before reaching a traditional search engine. ChatGPT, Perplexity, Google AI Overview, Gemini, Copilot: these platforms don't rank web pages, they synthesize answers. And to be cited in those answers, you need to master an entirely new vocabulary.
This glossary is not an academic dictionary. It's an operational tool designed for decision-makers, marketers, and digital teams who want to understand the mechanics of AI visibility and act accordingly. Each term is explained with its definition, its concrete business impact, and the actions you should take to leverage it.
AEO (Answer Engine Optimization), GEO (Generative Engine Optimization), the llms.txt file, Schema Markup, Knowledge Graphs, Topical Authority: these concepts are no longer reserved for technicians. They determine whether your brand exists or not in the answers your prospects receive when they ask questions to AI. Most companies don't yet master this vocabulary. That's an advantage for those who do.
Whether you're discovering the topic or looking to deepen your understanding of a specific concept, this glossary is your reference. It's updated regularly to reflect the rapid evolution of this ecosystem. For each term, you'll find a detailed article with examples, methods, and links to complementary resources.
AI visibility is a discipline in its own right that draws from SEO, semantics, content engineering, and artificial intelligence. This glossary bridges these worlds. It translates technical complexity into growth levers. Because ultimately, the point isn't to memorize these terms but to understand how they fit together to make your brand a reference that AI cites, recommends, and shares.
Each glossary entry is a complete page covering the definition, strategic context, practical implications, and implementation method. Terms are interconnected: when one concept references another, a link takes you directly to the detailed explanation.
If you're starting out, begin with the three foundational entries: AI Visibility, AEO, and GEO. These three concepts form the foundation for everything else. Then explore technical terms like Schema Markup and llms.txt to understand the concrete mechanisms.
For an industry-specific approach, check our industry pages that apply these concepts to your sector. And for practical step-by-step guides, head to our Resources section.
AEO is the practice of optimizing content so AI engines like ChatGPT and Perplexity cite your brand. Learn why AEO matters more than SEO alone.
Read definition →GEO optimizes your content for generative AI engines. Learn how it differs from SEO and AEO, and why your brand needs it now.
Read definition →llms.txt is a machine-readable file that tells AI models about your brand. Learn why it is the new robots.txt and how to implement it.
Read definition →Schema markup is structured data that helps search engines and AI understand your content. Learn why it is essential for AI visibility.
Read definition →AI visibility measures how often AI engines cite and recommend your brand. Learn why it is replacing traditional search visibility.
Read definition →Semantic SEO focuses on meaning and context rather than keywords. Discover how it powers AI visibility and builds topical authority.
Read definition →Knowledge graphs are how AI engines understand entities and relationships. Learn how to get your brand into the knowledge graph.
Read definition →Topical authority is how search engines and AI decide who the experts are. Learn how to build comprehensive topic coverage that AI trusts.
Read definition →Content clustering organizes your content into topic hubs that build authority. Learn how pillar-cluster models drive AI visibility.
Read definition →Entity SEO optimizes for concepts and their relationships, not just keywords. Learn how entities power AI understanding and visibility.
Read definition →Zero-click searches answer users directly on the SERP. Learn why over 60% of searches never result in a click and what it means for your brand.
Read definition →Perplexity AI is an answer engine that synthesizes web sources with AI. Learn how it works, why it matters, and how to get your brand cited.
Read definition →Technical SEO ensures search engines and AI can crawl, index, and understand your site. Learn the technical foundation of AI visibility.
Read definition →Internal linking connects your pages to build authority and help search engines understand your site. Learn why it is critical for AI visibility.
Read definition →Link building acquires backlinks from other sites to build domain authority. Learn how it has evolved for the AI visibility era.
Read definition →E-E-A-T is Google's framework for evaluating content quality. Learn how Experience, Expertise, Authority, and Trust impact AI visibility.
Read definition →Google AI Overviews are AI-generated answers at the top of search results. Learn how they work, their impact, and how to get featured.
Read definition →A SERP is the page search engines display after a query. Learn about SERP features, AI integration, and what it means for your brand visibility.
Read definition →Crawl budget is the number of pages search engines will crawl on your site. Learn how to optimize it for better indexing and AI visibility.
Read definition →Featured snippets display a direct answer above organic results. Learn how to win position zero and why it matters for AI visibility.
Read definition →AEO (Answer Engine Optimization) optimizes your content to be selected as a source by AI answer engines. GEO (Generative Engine Optimization) is more specific: it targets optimization for generative search engines like Perplexity and Google AI Overviews. In practice, both are complementary and form part of a comprehensive AI visibility strategy.
No. Traditional SEO remains essential for indexation, crawling, and ranking on transactional queries. AEO and GEO are additional layers that ensure your presence in AI-generated answers. Both approaches reinforce each other.
The llms.txt file is a new standard that tells language models (LLMs) how to interpret and cite your content. It's the equivalent of robots.txt for the AI era. It guides AI toward the most relevant information on your site and influences how they cite you.
Yes. Schema.org markup (JSON-LD) is one of the most powerful signals for LLMs. It provides explicit structure that machines use to understand your content's context. Sites with comprehensive Schema have significantly higher chances of being cited in generative answers.
Start with an audit: test what ChatGPT, Perplexity, and Gemini answer about your key queries. Then structure your content with Schema Markup, create an llms.txt file, and develop your topical authority. Our complete guide details each step. For personalized support, contact AISOS.
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