AI Search Glossary: 30+ Terms Every Marketer Needs to Know

The AI search landscape has spawned an entirely new vocabulary. Understanding these terms isn’t just academic—it’s essential for competing in a channel that Gartner predicts will capture 25% of traditional search volume by 2026.

Here’s every term you need to know, organized by category.

Optimization Frameworks

SEO (Search Everywhere Optimization)

The expanded definition of Search Engine Optimization that encompasses visibility across social media, generative AI platforms, and traditional search engines. The acronym stays the same, but the scope has expanded.

Some marketers use this term to emphasize that optimization efforts should target anywhere people search—not just Google.

GEO (Generative Engine Optimization)

The practice of optimizing content and brand presence to improve visibility in AI-generated responses. GEO focuses on earning citations and mentions from platforms like ChatGPT, Perplexity, and Google AI Overviews.

Unlike traditional SEO, GEO targets how AI models perceive and recommend your brand, not just page rankings.

AEO (Answer Engine Optimization)

Structuring content specifically for extraction by AI systems that provide direct answers. AEO emphasizes clear headings, self-contained passages, and content that directly addresses user questions.

The term predates the current AI boom—it originally referred to optimizing for featured snippets—but has expanded to cover AI-generated answers.

LLMO (Large Language Model Optimization)

Optimizing how LLMs understand and represent your brand across both training data and real-time retrieval systems. LLMO is the broadest term, covering everything from influencing training data to optimizing for live AI search.

Measurement Metrics

AI Visibility

How frequently and prominently your brand appears in AI-generated responses. This includes both explicit mentions and citations of your content as a source.

AI visibility is the core metric for GEO success. It measures whether AI systems know about your brand and recommend it to users.

The percentage of AI mentions your brand receives compared to competitors for a given set of queries. If you’re mentioned in 30 of 100 competitive queries while competitors are mentioned in 70, your share of voice is 30%.

SOV provides competitive context that raw mention counts lack.

Mention Rate

The frequency with which your brand name appears in AI responses across tracked queries. A high mention rate indicates strong AI visibility for your target topics.

Citation Rate

How often AI systems cite your content as a source when generating responses. Citations appear as clickable links to your pages within AI-generated answers.

According to AthenaHQ research, citation rate is a leading indicator—increases in citations precede gains in overall visibility by several weeks.

Zero-Click Result

When users obtain complete answers from AI responses without clicking through to any website. This phenomenon has grown with AI search, as platforms synthesize information directly rather than directing users to sources.

Zero-click results change the value equation: visibility itself becomes the outcome, not just a step toward traffic.

CTR (Click-Through Rate)

The percentage of users who click through to your site from AI-generated responses. In AI search, CTR is significantly lower than traditional search. iPullrank research found ChatGPT CTR of 3.8-5.4%, compared to approximately 40% for Google searches.

Technical Concepts

Prompt

The user’s input to an AI system. Prompts average approximately 20 words and small wording changes can significantly affect which brands AI recommends.

Understanding common prompts in your industry is essential for GEO—they’re the equivalent of keywords in traditional SEO.

Response

The AI-generated output following a prompt. Responses vary between identical prompts due to the non-deterministic nature of language models. A five-month Trackerly study found “no two answers were identical” even for the same query.

Citation

A source URL that AI includes in its response, functioning as the AI equivalent of a backlink. Citations indicate which content the AI deemed authoritative enough to reference.

Earning citations is a primary goal of GEO. Being cited signals trust to both the AI and users reading the response.

Mention

A reference to your brand name within AI-generated content, regardless of whether it includes a link. Mentions shape user perception even without driving direct traffic.

Not all mentions are equal—context matters. A positive recommendation carries more value than a neutral mention in a list.

RAG (Retrieval-Augmented Generation)

The architecture most AI search systems use. When the AI can’t answer from training data alone, RAG systems perform live searches to retrieve current information, then synthesize that information into responses.

RAG is where GEO optimization happens. Content that RAG systems retrieve gets incorporated into answers.

Query Fanout

How AI systems break single prompts into multiple related searches. A user asking “best CRM for startups” might trigger AI searches for “CRM software comparison,” “startup CRM features,” and “CRM pricing for small business.”

Understanding fanout helps you create content that captures related queries, not just exact matches.

Search Grounding

The process of tying AI responses to verifiable web sources. Grounded responses include citations and are based on retrieved content rather than training data alone.

AI platforms increasingly emphasize grounding to reduce hallucinations and improve accuracy.

Sliding Window

The method ChatGPT uses to read web content. Rather than processing entire pages, it retrieves text in sequential chunks of approximately 200 words. According to LLMRefs, this means “your page title and meta description determine whether ChatGPT decides to read further.”

The sliding window is why front-loading important content matters for GEO.

Content Architecture

Chunking

Breaking content into standalone sections that each answer a single question. Chunked content is easier for AI to extract and cite because each piece functions independently.

Effective chunking makes your content modular—AI can pull the specific answer it needs without processing irrelevant context.

AI Snippet

A short, quotable extract designed to stand alone when pulled by AI systems. AI snippets are self-contained answers that make sense without surrounding context.

Creating AI snippets within your content increases the likelihood of being cited.

Schema Markup

Structured data that helps AI systems understand your content’s meaning and relationships. Schema types like FAQ, HowTo, Product, and Organization provide machine-readable context.

Google notes that “structured data aids interpretability but does not guarantee inclusion.”

llms.txt

A markdown file that maps important pages on your site for AI discovery. Similar to robots.txt but specifically designed to guide AI crawlers to your most valuable content.

The format is relatively new and not universally supported, but early adoption may provide advantages.

Entity Recognition

How AI systems identify and connect organizations, products, people, and locations within content. Strong entity signals help AI accurately associate information with your brand.

Consistent naming, schema markup, and authoritative references strengthen entity recognition.

User Behavior Concepts

Memories

User preferences and information that AI assistants store to personalize responses. ChatGPT’s memory system stores approximately 33 facts per user, according to LLMRefs research.

Memories mean different users receive different responses to identical queries—personalization is built into AI search.

Session Context

Information from the current conversation that influences AI responses. Unlike memories, session context expires when the conversation ends.

Agentic Search

When AI systems perform multi-step research tasks autonomously, gathering information from multiple sources before synthesizing answers. This represents the next evolution of AI search behavior.

Content Strategies

Answer-First Content

Content structured to provide direct answers immediately, followed by supporting detail. This format aligns with how AI systems extract information.

The opposite of traditional content that builds up to conclusions through narrative.

Listicle

List-based content that AI can easily scan and extract. Formats like “10 Best X” or “5 Ways to Y” align with how AI systems organize information.

Listicles perform well in AI search because they provide clear structure and discrete, citable items.

Content Cluster

A group of interlinked content pieces covering different aspects of a topic. Clusters demonstrate topical authority to AI systems.

Single articles don’t build AI visibility. Comprehensive topic coverage through clusters signals expertise.

E-E-A-T

Google’s quality framework: Experience, Expertise, Authoritativeness, and Trustworthiness. While originally a Google concept, E-E-A-T signals influence AI visibility as well.

Content demonstrating genuine expertise and backed by credible sources performs better in AI search.

Platform-Specific Terms

AI Overviews

Google’s AI-generated summaries that appear at the top of search results for relevant queries. AI Overviews synthesize information from indexed pages and display supporting links.

Optimizing for AI Overviews involves traditional SEO plus GEO tactics.

Deep Research

ChatGPT’s feature for comprehensive multi-step research queries. Deep Research performs more extensive searches and analysis than standard queries.

Web Browsing Mode

When AI platforms actively search the web during conversations rather than relying solely on training data. This mode triggers RAG behavior where GEO optimization matters most.

GPTBot

OpenAI’s web crawler that indexes content for ChatGPT. Blocking GPTBot in robots.txt prevents your content from appearing in ChatGPT responses.

Other AI crawlers include ClaudeBot (Anthropic), PerplexityBot, and various others.

Emerging Concepts

Pay-Per-Crawl

A proposed model where AI companies compensate content creators when their crawlers access content. Cloudflare has proposed a marketplace implementation.

AI Labyrinth

A defensive technique that traps non-compliant AI scrapers in redirect loops while allowing legitimate visitors through. Cloudflare offers this as a protection option.

Inclusion Rate

The percentage of target queries where your brand appears in AI responses. This metric captures how consistently you achieve visibility across relevant topics.

Brand Visibility Score

A composite metric combining mention rate, citation rate, sentiment, and competitive positioning into a single indicator of AI search performance.

Putting It Together

The vocabulary of AI search reflects a fundamental shift in how people discover information and how brands compete for attention. Traditional SEO terminology—keywords, rankings, backlinks—doesn’t capture what matters in generative search.

Success in this new landscape requires understanding:

How AI systems retrieve and synthesize content (RAG, fanout, sliding window)
What metrics indicate performance (visibility, citations, share of voice)
What content structures AI prefers (chunking, snippets, answer-first)
How to build authority AI recognizes (E-E-A-T, entity recognition, content clusters)

Master this vocabulary and you’re equipped to compete in AI search. Ignore it and you’re optimizing for a game that’s already changing.

RivalHound tracks your AI visibility, citations, and share of voice across every major AI platform. Start monitoring your AI search presence today.