GEO
Generative Engine Optimization. Making a company appear, be described correctly and be recommended inside answers generated by AI systems. The broadest of the four terms.
GEO, AEO, LLMO, AI SEO: four names, one job. This guide explains what each term means, where they genuinely differ, and which parts of the work actually move a measurement.
GEO, AEO, LLMO and AI SEO are four names for the same discipline: making a company visible in the answers AI systems generate for buyers.
Generative Engine Optimization. Making a company appear, be described correctly and be recommended inside answers generated by AI systems. The broadest of the four terms.
Answer Engine Optimization. Emphasis on being the source an answer engine draws from, including AI Overviews and featured answers in search.
Large Language Model Optimization. Used mostly for what a model recalls without searching the web, which is the slowest part to change.
Umbrella label used by agencies adding AI visibility to an existing offer.
The only distinction that changes what you do is between answers grounded in a live web search and answers recalled from model memory. One new comparison page or review can influence a grounded answer within days. What a model knows without searching shifts over training cycles and responds mainly to the breadth of independent evidence about you. That is why an EntityRise audit does not mix these two with technical readiness: the visibility result comes only from measured answers, and the conditions around the brand are reported separately.
The work of GEO and AEO consists of four layers: an unambiguous entity, content for buyer questions, verifiable external evidence, and technical accessibility for AI crawlers.
One category, one audience, one sentence that a model can repeat without hedging. Structured identity data and consistent naming across your own surfaces.
Pages that answer the specific buyer questions in your category, including comparisons and objections, not generic blog volume.
Review profiles, named customer proof, editorial mentions and reference sources that appear in citations for your category.
Fetchability, rendering, indexability and consistency of your evidence pages.
Measure the same confirmed question set before and after, on a sealed test set, with brand-name questions excluded from the index. Anything else measures your own optimism. That is the whole argument for a reproducible audit rather than a rolling dashboard.
Instead of picking an acronym, look at the numbers: where you are visible, where you are cited, and what is missing.
Ask either one how they will measure the result, whether brand-name prompts count toward it and whether the test set is fixed between measurements. The answer tells you more than the label on the offer.
The work overlaps heavily with good SEO, but the measurement is genuinely different: there is no ranking position inside a generated answer, so you measure presence, prominence, description accuracy and citations instead.