AEO & GEO glossary

Plain-English definitions of the answer engine optimization (AEO) and generative engine optimization (GEO) terms that come up most — so you can talk about AI visibility without the jargon fog.

Answer Engine Optimization (AEO)

The practice of getting a business named and cited by AI answer engines when people ask them for recommendations, so you appear in the answer itself rather than only in a list of links.

Generative Engine Optimization (GEO)

The practice of optimizing content and web presence so generative AI engines include and cite you when they generate an answer. Used near-interchangeably with AEO.

Answer engine

An AI system that responds to a question with a synthesized answer rather than a list of links — for example ChatGPT, Perplexity, Gemini or Claude.

Large language model (LLM)

The type of AI model that powers answer engines. It generates text by predicting likely continuations, drawing on training data and, increasingly, live web sources.

AI visibility

How present, and how often named, a business is across AI answer engines when buyers ask relevant questions. The AI-era counterpart to search visibility.

AI-visibility score

A single measure of how often the answer engines name a business versus competitors for a defined set of questions, tracked per engine over time.

Citation

A reference an answer engine makes to a source or business when it generates an answer. Earning citations is the core objective of AEO and GEO.

Citation share

The proportion of AI answers, for a set of questions, that cite or name your business relative to competitors — the GEO equivalent of share of voice.

Entity

A distinct thing an AI can recognize and reason about — a business, person, product or place. Clear entity signals help engines classify and name you correctly.

Structured data (schema markup)

Machine-readable code (such as schema.org JSON-LD) added to a page so engines can reliably understand what it describes — an organization, product, article or FAQ.

AI overview

An AI-generated summary shown at the top of some search results, synthesizing multiple sources into a direct answer, often with citations.

Retrieval-augmented generation (RAG)

A technique where an answer engine retrieves relevant documents from the web or a database and uses them to ground its generated answer, improving accuracy and enabling citations.

Grounding

Tying an AI's answer to verifiable external sources rather than only its trained parameters. Grounded answers are more likely to cite specific businesses and pages.

Hallucination

When an AI states something confidently that is inaccurate or unsupported. Strong, corroborated entity signals reduce the chance an engine gets your details wrong.

Answer-shaped content

Content that states the answer to a question plainly and up front, then supports it — the format answer engines most easily extract and quote.