The short answer
This is a plain-language glossary of the AI search and AEO terms that matter most, grouped by concept so you can see how they connect rather than memorizing 30 definitions in a vacuum. The one relationship to hold in your head as you read: retrieval and structured data make your page eligible to be quoted, and third-party citations plus a consistent brand entity are what get you chosen. Everything else is detail hanging off that spine.
If you want the terms in context before you dive in, start with what answer engine optimization actually involves or compare AEO to GEO to SEO. Otherwise, read straight down: the sections move from core concepts to content, technical, measurement, and the engines themselves.
How the key terms connect
Before the definitions, here is the map. Traditional SEO earns a ranked link on a results page. AEO and GEO, which are the same discipline under two names, earn a citation inside the AI answer itself. That citation only happens if an engine can retrieve your page, extract a clear answer from it, and trust your brand as an entity, and that trust comes mostly from other sites, not your own.
Keep that structure in mind. The definitions below fill in each node.
Core concepts
Answer Engine Optimization (AEO). The practice of making your brand retrievable, trustworthy, and citable by AI answer engines like ChatGPT, Perplexity, and Gemini. Where SEO earns a ranked link on a results page, AEO earns a citation inside the answer itself. See what is answer engine optimization for the full discipline.
Generative Engine Optimization (GEO). Another name for AEO. The term comes from the academic research community; AEO is more common in marketing practice. Both describe the same goal: being surfaced and cited inside AI-generated responses. Read what is generative engine optimization if you want the origin of the term.
Answer engine. A tool that responds to a query with a synthesized, written answer rather than a list of links. ChatGPT, Perplexity, and Google AI Overviews are all answer engines. The distinction matters because these tools select and cite sources differently than traditional search algorithms do.
Large Language Model (LLM). The type of AI model that powers most answer engines. LLMs are trained on large corpora of text and learn to predict and generate language. They answer questions by drawing on patterns in training data and, in retrieval-augmented systems, from live fetched content.
Retrieval. The process by which an AI system fetches relevant external content before generating a response. Engines that retrieve content can surface pages published after their training cutoff and are more likely to cite specific sources. Being retrievable is the first prerequisite for being cited.
Retrieval-Augmented Generation (RAG). An architecture in which an LLM retrieves relevant passages from a document store or the live web before generating its answer. Most live AI search products use a form of RAG, which is why being retrievable and parseable is a prerequisite for being cited.
Grounding. Anchoring an AI response to specific retrieved sources so it can be verified. A grounded response names where its facts came from, which is the mechanism that produces citations.
Hallucination. When a language model generates a confident but factually incorrect statement by filling in gaps from pattern-matching rather than retrieved evidence. Well-grounded, source-backed content reduces hallucination risk and is preferred by retrieval-based engines.
Prompt. The question or instruction a user types into an AI tool. In AEO, "prompts" also refers to the set of tracked questions you run across engines to measure citation share. Understanding the exact language your buyers use is the foundation of any AEO content strategy.
Entity. A distinct, named thing (a brand, person, product, or concept) that a model recognizes and can reason about. Consistent naming and facts across your site and third-party sources strengthen your brand entity and make you more likely to be recommended confidently. Weak or contradictory entities get hedged answers.
Content and technical
Answer-first content. A writing approach in which the direct answer to the target question appears in the first two to four sentences, before any context or explanation. AI engines extract passages to quote; answer-first structure ensures the passage they pull contains the point, not preamble.
Schema markup. Code added to a web page that describes its content in a vocabulary (schema.org) machines can read without ambiguity. It gives an engine your facts directly instead of forcing it to infer them from prose, which makes extraction more reliable. Common types for AEO include Article, FAQPage, Organization, and Product. See schema markup for AI search.
Structured data. Any data formatted so a machine can parse it reliably. In web contexts, this usually means schema.org markup in JSON-LD format embedded in the page. Structured data is the technical layer that makes your facts unambiguous to an engine.
JSON-LD. JavaScript Object Notation for Linked Data. The format Google and most AI engines prefer for schema markup. JSON-LD is embedded in a script tag in the page head and describes the page's content in structured key-value pairs.
Knowledge Graph. A database of interconnected entities and facts. When a model has a strong, consistent entity for your brand in its knowledge base, it cites you more confidently. This is why entity consistency across your site and third-party sources matters.
llms.txt. A proposed standard file, placed at /llms.txt on a domain, that gives AI crawlers a clean, markdown-formatted summary of the site's content and structure. Analogous to robots.txt but written for language models. It is not yet universally adopted but is gaining traction as a way to guide how AI tools read a site. See what is llms.txt.
robots.txt. A standard file at /robots.txt that instructs web crawlers which pages they may and may not fetch. Critically for AEO, many brands accidentally block AI-specific crawlers (GPTBot, ClaudeBot, PerplexityBot) in their robots.txt rules, silently opting out of being cited.
AI crawler. A crawler operated by an AI company to fetch web content for training data or live retrieval. Key crawlers include GPTBot and OAI-SearchBot (OpenAI and ChatGPT), ClaudeBot (Anthropic), PerplexityBot (Perplexity), and Google-Extended (Google AI products). Each can be allowed or blocked independently in robots.txt.
Featured snippet. A boxed excerpt at the top of a traditional Google results page that directly answers a query. Featured snippets and AI citations share content requirements (direct answers, clean structure) but serve different surfaces; winning one does not guarantee the other.
AI Overviews. Google's answer-engine layer, surfaced at the top of search results pages for many queries. AI Overviews generate a synthesized paragraph and cite several source pages. Optimizing for AI Overviews overlaps with broader AEO but has Google-specific nuances around E-E-A-T signals. See Google AI Overviews.
TL;DR. "Too long; didn't read." A short summary placed near the top of a long piece. AI engines often extract this when generating a high-level answer, so a well-written TL;DR increases the chance the engine quotes your words rather than paraphrasing them.
Long-tail query. A specific, multi-word search query with lower volume but higher intent. Long-tail queries matter disproportionately in AI search because users ask full questions rather than short keyword strings, and content that answers those questions precisely tends to get cited at the moment of highest purchase intent.
Semantic search. Search that interprets the meaning and intent behind a query rather than matching keywords literally. Both modern search engines and AI answer engines use semantic understanding. This is why AEO content should be written to answer real questions, not to repeat keyword phrases.
Zero-click search. A search resolved on the results page itself without the user clicking through to any site. About 68 percent of Google searches now end without a click, per SparkToro's 2026 analysis of Similarweb clickstream data, up from about 60 percent in 2024. AI answers accelerate this behavior, making citation inside the answer more valuable than a ranked link the user never visits.
Measurement
Share of voice. The percentage of tracked prompts on which your brand is mentioned across the major engines, measured relative to competitors. It is a primary metric for AI search presence: high share of voice means you are named often; low share of voice means you are rarely or never in the answer.
Citation rate. How often your brand is cited as a source (linked, footnoted, or explicitly attributed) across tracked prompts, expressed as an average per prompt. A citation is stronger than a mere mention because it directs the reader back to your page.
Mention rate. How often your brand name appears in AI-generated answers across tracked prompts, regardless of whether a source link is included. Mentions indicate brand recognition; citations indicate source authority. Both matter, but citations have more downstream impact on traffic.
Prompt volume. The estimated number of times a given question is asked across AI engines in a given period. Analogous to search volume in traditional SEO. Prioritizing prompts with high volume and strong buyer intent is the starting point for an AEO content strategy.
Sentiment. In AEO measurement, how positively or negatively an AI engine frames your brand when it mentions or cites you. Consistently neutral or positive framing is the baseline. Negative sentiment, for example an engine qualifying a recommendation with a concern, signals a trust or reputation issue to investigate.
The engines
ChatGPT. OpenAI's conversational AI product and the most widely used answer engine. ChatGPT with search browses live web content and cites sources; the base model answers from training data. Both surfaces matter for AEO. See how to rank in ChatGPT.
Perplexity. An AI answer engine that retrieves and cites live web sources for nearly every query. Its transparent source display makes it a useful benchmark for testing whether your content is being retrieved and cited. See how to show up in Perplexity.
Gemini. Google's AI model, surfaced as AI Overviews in search results and as a standalone product. Gemini draws on Google's index and knowledge graph, so E-E-A-T signals and traditional authority carry more weight here than in other engines. See how to show up in Google Gemini.
Terms most people confuse
Three pairs trip up almost everyone new to AI search. Here is the clean distinction for each.
| These two | Are not the same because |
|---|---|
| AEO vs GEO | Nothing. They are two names for the same discipline. AEO comes from marketing, GEO from academic research. Do not overthink it. |
| Mention vs citation | A mention names your brand in the text. A citation links your page as the source. Citations are stronger and more actionable to track. |
| SEO vs AEO | SEO earns a ranked link on the results page. AEO earns a citation inside the AI answer. You can win one and lose the other. See AEO vs SEO. |
| Retrieval vs training data | Retrieval fetches live content at query time. Training data is baked in at the model's cutoff. Retrieval is how new pages get cited fast. |
The one number that reframes the whole glossary
Most of these terms point back to one uncomfortable fact: you do not win AI search primarily on your own website. When we aggregated the source domains AI engines cited for live client brands over a recent 90-day window, a brand's own domain was a small minority of what got quoted.
That is why so much of this glossary is about entities, citations, and third-party trust rather than on-page tricks. Retrieval, schema, and answer-first content get you eligible to be quoted. Being named across the sources an engine already trusts is what gets you chosen. For the underlying data and what to do about it, read how to rank in ChatGPT and why isn't my brand in AI search.
Watch: a primer on Answer Engine Optimization
If the terms above are new, this short explainer from Ahrefs is a solid overview of what AEO is and why it matters before you go deeper.
Key takeaways
- AEO and GEO are the same discipline under two names; do not treat them as competing strategies.
- The spine of AI search: retrieval and structured data make you eligible to be quoted, and third-party citations plus a consistent brand entity get you chosen.
- A mention names your brand; a citation links your page. Track citations, because they carry more downstream traffic.
- Your own website is only 2 to 6 percent of the sources AI engines cite in your category, so most of the work happens off-site.
- Measure AI search directly with share of voice, mention rate, and citation rate by prompt, not with normal analytics, because AI-influenced buyers arrive as direct or branded traffic.
Where to start
If this glossary surfaced gaps in how your brand shows up across these engines, an AI visibility audit from AEO Labs maps your current citation share against these exact metrics and shows which third-party sources to go win. From there, our program and digital PR and citations work close the gaps systematically. If you are still mapping the landscape, read what is generative engine optimization and does SEO still matter with AI search next.