Glossary
Every term you need to talk about AI visibility precisely, defined in one sentence and then explained properly
An AI citation is a link or source reference an answer engine attaches to a generated answer, showing where a claim came from. Citations are the clearest measurable signal that a specific page influenced what the model told the user.
AI Overviews is Google's AI-generated summary that appears above the traditional blue links on a search results page. It answers the query directly and links to a small set of cited sources, which reduces the share of clicks reaching the results below it.
An answer engine is a system that responds to a question with a written answer rather than a list of links. ChatGPT, Google AI Overviews, Gemini, Claude, Perplexity, Copilot, Meta AI, Mistral, DeepSeek, Qwen and Kimi are the answer engines most brands need to track.
Answer Engine Optimization (AEO) is the practice of making a brand visible, accurately described and cited inside the answers that AI systems such as ChatGPT, Google AI Overviews, Gemini, Claude and Perplexity generate, rather than only ranking in a list of links.
A brand entity is the structured, machine-readable identity of a brand: its name, category, products, people, locations and relationships, consistently expressed across its own site and third-party sources so that AI systems recognise it as one thing.
Generative Engine Optimization (GEO) is the practice of influencing how generative AI models describe, recommend and cite a brand when they produce an answer. It is used interchangeably with Answer Engine Optimization; GEO emphasises the model, AEO emphasises the answer.
Grounding is the process of tying a model's generated answer to retrieved source documents, so that claims can be traced back to real content instead of coming only from model weights. Grounded answers are the ones that carry citations.
A hallucination is a confident but false statement produced by an AI model. For brands the practical risk is a model inventing pricing, features, policies or comparisons that were never true, and repeating them to buyers as fact.
llms.txt is a plain-text file placed at the root of a website that gives large language models a curated, markdown-formatted summary of the site and its most important pages. It is a proposed convention, not a standard, and it complements rather than replaces robots.txt and sitemap.xml.
A Presence Score is a single 0 to 100 metric summarising how present a brand is inside AI answers, combining how often it is mentioned, how highly it ranks within each answer and how often its pages are cited, measured across a fixed set of prompts and engines.
A prompt set is the fixed list of questions a brand tracks across answer engines, chosen to represent how real buyers ask about its category. Holding the set stable is what makes AI visibility measurements comparable over time.
Retrieval-augmented generation (RAG) is an architecture in which a model searches a corpus for relevant documents and writes its answer from those documents. Most answer engines use some form of RAG, which is why what is published on the open web still decides what they say.
Share of voice in AI is the proportion of answers in a given prompt set where a brand is named, relative to the brands it competes with. It answers the question of who AI recommends in a category, not just whether you appear.
A technical AEO audit checks whether AI crawlers can reach, render and correctly interpret a site's pages: crawler access rules, server-rendered content, heading structure, structured data, canonical and language signals, and page freshness.
A zero-click search is a search that ends without the user visiting any result, because the answer was delivered on the results page itself. AI-generated answers have sharply increased the share of searches that end this way.
Step two is seeing your own numbers across every answer engine
