SEO dictionary for AI

With the rise of generative AI, SEO enters a new stage. It's no longer enough to optimize for Google, you need to understand how language models (LLMs) work, how they select information, and how AIs present their answers.

This dictionary was created with a dual purpose:

• Educational: to explain emerging concepts in SEO for AI.
• Strategic: to help you adapt content, structures, and technologies to new generative environments.

It’s the natural companion to our other resources:

• SEO Dictionary
• SEM / PPC Dictionary

Concept index by category

• 1. Optimization for generative AI
• 2. AI architectures and techniques
• 3. Visibility and response strategy
• 4. Semantic and structural SEO
• 5. AI-friendly formats and multimodal content
• 6. Testing, citations, and evolution

1. Optimization for generative AI

LLMO – Large Language Model Optimization

Optimizing content to be understood, selected, and recommended by LLMs such as ChatGPT, Claude, or Gemini. Similar to traditional SEO, but designed for conversational interfaces and generative answers.

GEO – Generative Engine Optimization

Strategies to appear as a source within generative search engines (like Google SGE or Perplexity). Requires reliable, structured, and “citable” content.

GAIO – Generative AI Optimization

Broader optimization for multimodal generative AI (text, voice, image). Includes writing best practices, technical SEO, and semantic structure to make content retrievable and AI-usable.

Prompt SEO

Optimization so that your content can be used as a response to a prompt or query within a generative system. Requires clear syntax, descriptive headings, and reusable content blocks.

RAG-ready content

Segmented, clear, and modular content, designed to be retrieved and used within RAG systems. Ideal for AIs that generate answers based on external documents.

2. AI architectures and techniques

Vector Embeddings

Numerical representations of content that allow retrieval based on semantic similarity. Fundamental for AI-driven search engines and tools like ChatGPT with browsing.

RAG – Retrieval-Augmented Generation

An architecture that allows AI to consult external documents before generating a response. The better your content is retrieved and understood, the more likely it is to be used and cited.

Vector SEO

Techniques to improve how your content is represented in vector databases. Achieved through semantically rich, structured, and contextualized text.

GPT – Generative Pre-trained Transformer

A language model architecture based on transformers, pre-trained on massive datasets and capable of generating coherent, contextual text. GPTs are the foundation of many generative AI systems and conversational models, and understanding how they process and select information is key to optimizing content for AI visibility.

Browsing AI

The ability of language models to access and read live web content in real time. It opens new SEO opportunities, as AI can now discover, interpret, and cite updated pages beyond its original training data.

Fine-tune SEO

Preparing content to be useful in training custom AI models, such as corporate bots or internal AI-powered search engines.

3. Visibility and response strategy

AEO – Answer Engine Optimization

Techniques to rank as the best answer to direct questions via assistants, voice search, or featured snippets. Essential for intent-based searches seeking “an answer,” not just a list of links.

AI Overviews (Google)

A Google SGE feature that generates an AI-generated summary in response to a query. Sources selected can gain major visibility, though they don’t always receive direct clicks.

AI Mode

A search or navigation mode focused on AI interfaces. Instead of a SERP, the user gets a conversation. Requires rethinking your content’s information architecture for AI.

Zero Click SEO 2.0

An evolution of the "Zero Click" concept: AI now provides complete answers without the user needing to visit your website. The competition is for authorship, mentions, and perceived authority.

Pre-click Influence

Strategies to influence how AI presents your content before the user decides whether to click. Closely linked to EEAT, Schema markup, and the visual/textual structure of your content.

4. Semantic and structural SEO

LSO – Language Search Optimization

Adapting content to the natural language used by users and AI. Ideal for conversational queries, open-ended questions, and FAQs.

LEO – Language Engine Optimization

Optimization for proprietary language engines, such as corporate AI assistants. Prioritizes informative, modular, and context-rich writing.

Semantic SEO++

An advanced form of semantic SEO that uses ontological relationships, enriched data, and explicit semantic frameworks. Designed for AI comprehension and connectivity.

Schema for LLMs

Advanced structured data techniques to help LLMs better understand your content. A complement to Schema.org, designed for machine readability.

Knowledge Graph Optimization (KGO)

Techniques to control, enhance, or create custom entities within knowledge graphs used by both Google and AI models.

5. AI-friendly formats and multimodal content

SCO – Synthetic Content Optimization

Best practices for human-in-the-loop AI-generated content. Aims to avoid generic, repetitive, or low-quality text.

Conversational SEO

Content designed for dialogue-based environments. Structured FAQs, question-answer flows, and formats that fit within conversational responses.

Multimodal SEO, Cross-platform SEO

SEO adapted to content that multimodal AIs can interpret video, audio, images, graphics, and text. Each format must “speak AI.”

Local GEO

Local adaptation of Generative Engine Optimization. For example: “best electrician in Sabadell.” It’s local SEO, but tailored for generative search responses.

6. Testing, citations, and evolution

Citations SEO

Strategies to get your content cited (with a visible URL or brand mention) in generative answers. Valuable for brand authority and exposure.

GAI Testing & Audit

Methods for assessing how your content appears in generative answers. Includes prompt testing, citation analysis, and competitive benchmarking.

AI-first Indexing

A forward-looking hypothesis: AI will read and classify your content before traditional search engines do. Structuring content for machine understanding will be key.

Ongoing evolution

This dictionary is a living snapshot of SEO in the age of artificial intelligence. As of today, many of these terms are still evolving and new ones appear almost weekly.

That’s why this resource is open-ended. We’ll continue to build, revise, and expand it as technologies, models, and platforms reshape the way we search and the way we are found.

Would you add another concept?
Let us know, share it, and help us grow this new language of SEO for AI.