Answer engine optimisation (AEO), generative engine optimisation (GEO) and AI SEO are overlapping terms for making a brand visible in AI-generated search results. AEO focuses on being the cited source for a direct answer, GEO on being named inside synthesised responses, and AI SEO is the umbrella covering both alongside traditional search.

The vocabulary in this category is a mess, largely because four groups coined competing terms simultaneously. This glossary defines each one as it is actually used, and flags where the definitions genuinely conflict.

The three main terms

AI SEO

The broadest term. Covers all work aimed at visibility in AI-influenced search, including traditional SEO where it feeds AI systems. Used loosely, and often simply as a rebrand of ordinary SEO services. When a business searches this term they usually mean “help me be visible in AI search” without a strong view on mechanism.

GEO — Generative Engine Optimisation

Optimising for systems that generate a new answer by synthesising multiple sources: ChatGPT, Gemini, Perplexity, Google AI Overviews. The output is original text, and your goal is to be one of the brands named within it. Coined in academic work in 2023 and now the most widely adopted term in the industry.

AEO — Answer Engine Optimisation

Optimising to be the cited source for a direct answer. Predates GEO — it originally described featured snippets and voice assistant answers — and has been retrofitted to AI. Where GEO is about being synthesised into a recommendation, AEO is about being the attributed source underneath it.

The honest position on AEO vs GEO: in practice, most agencies use them interchangeably and the distinction is thinner than either camp claims. The useful separation is that AEO leans toward factual, extractable, single-answer queries, while GEO leans toward comparative and recommendation queries. If you are choosing one term for your own marketing, GEO currently has more search volume and clearer meaning.

Related optimisation terms

LLMO / LLM Optimisation — Optimising specifically for large language models. Functionally a synonym for GEO; lower search volume and mostly used by technical practitioners.

LLM Visibility — How visible a brand is inside large language model outputs. Measurement-focused rather than tactic-focused. Genuine search demand: 350 UK / 1,200 US monthly.

AI Visibility — The broadest measurement term, covering presence across all AI surfaces. The most searched of the measurement terms at 700 UK / 3,300 US, and notably low difficulty.

SEO — Search Engine Optimisation — The parent discipline. Ranking pages in results lists. Not obsolete, and remains the foundation all of the above depend on.

Local SEO — Geographic search optimisation. Increasingly relevant to GEO because AI answers frequently include location qualifiers.

Technical SEO — Crawlability, indexation, speed, structure. Directly determines whether AI systems can access you at all.

Platform and system terms

Answer Engine — Any system returning a direct answer rather than a list of links. Includes AI chat interfaces and older featured-snippet mechanisms.

Generative Engine — A system producing original synthesised text in response to a query.

AI Overviews — Google’s AI-generated summaries appearing above organic results. Formerly Search Generative Experience (SGE). The single largest AI search surface by reach.

LLM — Large Language Model — The underlying technology. GPT, Claude, Gemini and Llama are examples.

RAG — Retrieval Augmented Generation — The architecture where a model retrieves live documents before answering, rather than relying only on training data. This is why current, crawlable content matters: RAG systems fetch it at query time.

Grounding — Anchoring a model’s answer to retrieved sources rather than training data alone. Grounded answers carry citations, which is why they matter commercially.

Zero-Click Search — A search resolved without visiting any website. Rising sharply, and the main reason traffic can fall while visibility rises.

User interacting with an AI chatbot on a smartphone alongside a laptop, reviewing AI-generated information and productivity suggestions across multiple devices.

Measurement terms

Citation — An explicit source attribution in an AI answer, usually linked. The clearest measurable GEO outcome.

Mention — A brand named in an answer without a linked citation. Harder to track, often more commercially valuable, because a recommendation carries more weight than a footnote.

Share of Voice (AI) — Your appearance rate across a defined prompt set, relative to competitors. The most useful competitive GEO metric.

AI Visibility Score — A composite measure of how often and how prominently a brand appears across AI platforms. No industry standard exists yet, so scores are not comparable between tools.

Prompt Tracking — Monitoring specific queries over time, the AI equivalent of rank tracking.

Impression (AI) — An instance of a brand appearing in a generated answer.

Branded Search Lift — Growth in searches for your brand name. One of the cleanest downstream indicators that AI systems are recommending you, because people who receive a recommendation then search the name.

Content and technical terms

Answer-First Structure — Opening a page with a short, self-contained answer before any other content. The highest-return structural change for AI visibility.

Extractability — How easily a passage can be lifted from your page and used in an answer without losing meaning.

Entity — A distinct thing a search system recognises: a company, person, product or place. Entity clarity determines whether systems can confidently describe you.

Knowledge Graph — A structured database of entities and their relationships. Feeds both traditional and AI search.

Schema Markup — Structured data explaining what a page contains. Machine-readable context.

llms.txt — An emerging convention: a root-level plain-text file describing your site to AI crawlers, analogous to robots.txt but declarative rather than restrictive.

GPTBot / PerplexityBot / ClaudeBot — The crawlers used by OpenAI, Perplexity and Anthropic. If blocked, you are invisible to those platforms regardless of everything else.

Semantic Search — Matching on meaning rather than exact keywords. The mechanism behind the shift from keyword phrases to conversational queries.

Topical Authority — Consistent demonstrated expertise across a subject rather than a single page. Weighted heavily by AI systems.

E-E-A-T — Experience, Expertise, Authoritativeness, Trustworthiness. Google’s quality framework. Directly relevant to whether AI systems treat you as citable.

So which term should you actually use?

For your own marketing, this is a positioning decision rather than a technical one.

Use “AI SEO” if you want the broadest reach and your audience is not deeply technical. It carries the most volume — 1,900 UK / 8,500 US — and requires the least explanation.

Use “GEO” if you want to signal specialism and your audience is marketing-literate. Better-defined meaning, strong and growing demand, and the term the industry is settling on.

Use “AEO” with caution. The acronym is genuinely ambiguous — it is also a clothing retailer’s ticker symbol and an airport code — so always write it out as “answer engine optimisation (AEO)” on first use.

Avoid “LLMO” unless your audience is technical. Low volume, and it needs explaining every time.

Key takeaways

  • AEO, GEO and AI SEO overlap heavily; the distinctions matter more for positioning than for practice.
  • GEO is the term the industry is converging on and has the clearest definition.
  • AEO is ambiguous as a bare acronym and should always be written out on first use.
  • AI visibility is the dominant measurement term; no standardised scoring exists yet.
  • RAG architecture is why current, crawlable content matters — systems fetch sources at query time.