GEO, AEO, LLMO, and AI SEO describe overlapping work. Definitions vary by author and vendor. This chapter explains the usual meanings and states how this guide uses the terms.
The terms, one by one
GEO: generative engine optimization
Generative engine optimization (GEO) was introduced in a 2023 paper that tested ways to improve source visibility in generated answers. The authors reported gains of up to 40% in their experiments. That result belongs to the paper’s benchmark and methods; it is not a forecast for an individual website."GEO: Generative Engine Optimization" (Aggarwal et al.), the paper that introduced the term and the GEO-bench evaluation set. The 40% figure is the paper's best case, and gains varied widely by domain.
The term GEO can be confused with geographic targeting. It can also leave the scope unclear: a project may involve content editing, search access, measurement, or all three. Name the actual work in proposals and reports.
AEO: answer engine optimization
Answer engine optimization (AEO) emphasizes appearing in direct answers. The term also applies to work on featured snippets and voice answers. In an AI project, specify whether the objective is a citation, a brand recommendation, or an accurate answer to a question.Semrush's "What Is Answer Engine Optimization" is representative of how the industry defines the term and its citation emphasis.
LLMO: large language model optimization
Large language model optimization (LLMO) emphasizes what a language model generates. The surrounding product also matters. Instructions, available tools, retrieved sources, and conversation context can affect the response.
AI SEO, and the rest
AI SEO can mean using AI tools to perform SEO or improving visibility in AI search. State which meaning applies. Terms such as “agentic search optimization” usually extend the discussion to software that browses or performs tasks on a user’s behalf.
How terminology varies
Practitioner surveys show that these names are used inconsistently. Their results describe the surveyed groups at a particular time. They do not establish a single accepted definition.Search Engine Land's practitioner survey on what the discipline is called.Search Engine Land's follow-up naming research on recognition, usage, and sentiment across the candidate terms.
Search-volume estimates also depend on the tool, market, and measurement date. Use them to study the language customers search for, rather than to decide which term is technically correct.Tracemetry's "State of AI search demand 2026", using DataForSEO keyword volumes captured May 2026. Volumes are US, Google Ads index, and will have moved since.
The terms used in this guide
This guide uses three terms:
- AI search describes the information-seeking activity and products using generated responses.
- AI search visibility describes the observed mentions, recommendations, citations, and their accuracy.
- AI search optimization describes the work intended to improve those outcomes. Paid and organic results are measured separately.
Keep work and results separate in reports. Publishing corrected business information is a completed task. An increase in accurate answers is an observed result. One does not establish the other without measurement.
The translation table
Use this table to compare the terms:
| When you see | The writer usually means | This book says |
|---|---|---|
| GEO | All optimization aimed at AI answers | AI Search Optimization |
| AEO | Being the cited answer to specific questions | Citation and prominence work |
| LLMO | Influencing what the model itself says | Memory-side work |
| AI SEO | Either this discipline or AI-assisted classic SEO; check | AI Search Optimization, or "AI tools for SEO" |
| AI visibility, LLM visibility, share of model | The measurable outcome | AI search visibility |
| Answer engine, generative engine | The products composing answers | AI search, or the platform by name |
For the practical comparison, read SEO and AI Search Optimization. The glossary provides shorter definitions.