Someone asked me recently which of the three they needed to buy. Their agency had quoted separately for AEO and GEO, and a consultant had pitched LLMO on top. Three strategies, three acronyms, one confused buyer holding three proposals for what turns out to be the same job.
The acronym soup is a real problem in our industry right now. A Reddit thread asking whether we are measuring four different things or one thing four times captured it better than most articles do. So here is the plain-English map, where each term came from, and the honest verdict on how many you actually need.
The Short Version
LLMO, GEO and AEO are three names for overlapping work: making your content findable, understandable and citable by search engines and AI assistants. AEO (Answer Engine Optimisation) focuses on getting your content extracted as direct answers. GEO (Generative Engine Optimisation) focuses on visibility inside AI-generated responses. LLMO (Large Language Model Optimisation) is the umbrella term for optimising how large language models retrieve, understand and cite you. The definitions differ at the edges. The actual work converges almost completely: answer-shaped content, consistent entities, structured data, citable sources and fresh information. If you buy one coherent practice, you get all three.
LLMO. Large Language Model Optimisation
LLMO covers the widest ground. It is the practice of making your content, entity signals and data easy for large language models to retrieve, understand and cite. When someone asks ChatGPT, Perplexity or Google's AI Overviews a question in your area of expertise, LLMO is what determines whether your business appears in the answer.
The term came out of the practitioner community rather than academia, which is why its boundaries are fuzzy. Some use it narrowly for LLM citation work. Others use it for everything touching AI systems, from crawler access to voice assistants. I use it as the umbrella because it names the mechanism rather than the channel. My deeper guide to what LLMO is covers the full discipline.
GEO. Generative Engine Optimisation
GEO has the most respectable origin story of the three. The term was formalised in a 2023 research paper by teams at Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi. Not my work, for the record. But its core finding is worth knowing. The paper proposed the first general framework for optimising content for generative engines, and adding statistics, quotations and authoritative sources to content measurably improved how visible that content was inside AI-generated responses.
The tested tactics from that paper are worth listing because they became the playbook. Add relevant statistics. Quote authoritative sources. Use concrete data instead of vague claims. Say where the numbers came from. Simple levers, measurable effects. The same levers this page is built on.
That finding has aged well. It is effectively the research case for everything on this page. GEO is usually defined as optimising for visibility and citation in AI-powered search results, and by that definition it sits inside the LLMO umbrella.
AEO. Answer Engine Optimisation
AEO is the oldest idea in the list wearing the newest name. It is the practice of structuring content so answer engines can extract and display it as a direct answer. Think featured snippets, People Also Ask boxes, and the answer paragraph an assistant reads aloud. Its heritage is snippet optimisation, which SEOs were doing a decade before anyone said "answer engine".
The boundary question is whether AEO includes AI-generated answers or only direct extractions. Vendors argue both ways. Practically it does not matter much. The optimisation work is the same: lead with the answer, structure it clearly, mark it up, cite your sources. My guide to answer engine optimisation covers the mechanics.
What Each Term Looks Like in Practice
Definitions blur fast, so here is what each label looks like on a real page.
An AEO-shaped page opens with the answer. Someone searches "how long does a home insurance claim take" and the paragraph under the first heading is a forty-word answer that a featured snippet or an assistant can lift verbatim. The structure does the work. No tricks. The question is asked in the heading, and the answer arrives before the explanation.
A GEO-shaped page carries citable material. Specific statistics with their sources named, quotations from identifiable people, comparisons drawn from real data. The 2023 research found these elements measurably improved visibility inside generated responses, which is exactly why a stats page earns AI citations while a two-thousand-word opinion piece usually earns none.
An LLMO-shaped presence goes beyond the page. The same business facts appearing everywhere. Consistent entity naming across your site, your directory listings and your profiles. Schema that describes your organisation without ambiguity. When a model assembles an answer about your market, those signals decide whether your business exists in its world or not.
One page can be all three at once. The good ones usually are.
Where They Overlap and Where They Do Not
Draw the honest map and it looks like this. AEO is the narrowest: extractable direct answers. GEO is wider: citation and visibility across AI-generated responses. LLMO is the widest: everything about how language models retrieve, understand and represent you. Each contains the others.
Now the part the comparison guides skip. The task lists converge almost completely.
- Answer-shaped content with clear, self-contained definitions
- Entity consistency, so the same business facts appear everywhere
- Structured data markup that machines can parse
- Named sources, statistics and quotations that systems can lift
- Fresh information, because both people and models prefer current data
- Crawlable, fast, well-architected sites
Procurement rule of thumb. If a proposal separates these into three line items, ask which concrete tasks differ between them. If the answer is "different specialists", ask to see the output of each. Nine times out of ten the outputs are the same content and the same markup, presented twice.
Do You Need All Three?
No. You need one coherent practice executed well. The question to ask any provider is not "do you do AEO or GEO" but "show me what changes in my content and my technical setup, and show me a page of yours that AI systems actually cite."
What to hire for depends on your situation. If you are choosing a specialist, the skill set behind all three labels is identical: structured content, entity strategy, schema, and an obsession with sources. My LLMO services are built on exactly that stack. If you are weighing tooling and people, my comparison of AI SEO agents vs SEO agencies walks through what to automate and what to keep human.
What does one coherent practice include in a contract. A technical audit covering crawlability and schema. Content work around answer blocks and entity consistency. A citation and visibility routine. Monthly measurement across classic and AI surfaces. Write those four deliverables into the scope and no acronym can inflate the invoice.
One naming tip. If you are hiring, search the market by all the terms, because talent labels itself inconsistently. If you are selling, use the term your buyers use. In Spain "AEO" and "IA" sell. In the US "GEO" is the fashionable one this year.
How We Ended Up With Three Names for One Job
Follow the money and the naming makes sense. Vendors need differentiated products. Agencies need differentiated proposals. Researchers need terminology that cites well in papers. GEO won the academic pedigree because it was born in one. AEO won the European market because answer engines were the local talking point. LLMO won the practitioner crowd because it names the mechanism honestly.
None of that changes the work, but it does change what you pay. The same audit described three ways looks like three deliverables on three invoices. The defence is simple. Name the deliverables in your contract in plain language. Audit, content restructure, schema implementation, citation tracking. When the outputs are named, the acronyms stop being billable.
What Actually Changed About the Work
Here is what separates the label debate from reality. I track AI citations across my own and client sites through Search Console's Generative AI reporting. In the last full 28-day window I measured, AI features drove 204 impressions across 44 pages, growing 66% month over month in weekly trend. The pages winning citations shared the same traits the 2023 GEO paper identified: direct answers, named sources, specific numbers.
The work that earns citations is not mysterious. Define terms plainly. Answer one question per section. Cite where your numbers come from. Keep the facts current. The acronyms describe marketing positions around that work, but the daily routine is concrete. One answer block per section. One source per statistic. One entity definition everywhere your business appears. Do that consistently and the labels stop mattering. My AI search adoption statistics show how fast this layer became measurable, and my guide to getting cited in Google AI Overviews is the practical how-to.
Red Flags When Someone Sells You an Acronym
Three warning signs in proposals. The first is a separate line item per acronym without distinct deliverables underneath. The second is a definition that changes between the sales call and the contract. The third is a guarantee attached to any of it. Nobody controls how ChatGPT or Google composes an answer, and anyone promising a citation is selling something other than SEO.
The honest version is simpler than the pitch. Ask what changes on your site and in your data. Ask for one page of theirs that AI systems actually cite. Ask how they measure it. Clear answers to those three questions are worth more than any glossary, including this one.
Frequently Asked Questions
What does LLMO stand for?
LLMO stands for Large Language Model Optimisation. It is the practice of making your content, entity data and sources easy for language models to retrieve, understand and cite. It is the umbrella term covering what GEO and AEO describe separately.
Is GEO the same as LLMO?
Not exactly, but the work overlaps heavily. GEO (Generative Engine Optimisation) targets visibility inside AI-generated responses and comes from a 2023 research paper by Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi. LLMO covers that plus how models understand your entity overall. GEO is a subset of the job LLMO names.
What is the difference between AEO and GEO?
AEO (Answer Engine Optimisation) targets direct answer extraction, in the featured snippet tradition. GEO targets citation and visibility in generated responses. In practice both are won with the same tactics: answer-first content, structure, and sourced facts.
Do I need to invest in all three separately?
No. The task lists are nearly identical. Invest in one coherent practice covering answer-shaped content, entity consistency, structured data and citations. Ask providers what concretely changes on your site, not what acronym they use.
Which term should I use?
Use the one your market uses. "GEO" leads in US search volume this year. "AEO" has strong European usage. "LLMO" carries the highest commercial intent. For hiring and buying, search all three, because talent and vendors label the same work differently.
Is AEO just featured snippets with a new name?
Its heritage is snippet optimisation, but its scope has grown to include voice assistants and AI answer extraction. The underlying work is the same. The distribution surface is what changed.
Are GEO and AEO the same as AI SEO?
AI SEO is the informal umbrella for all of it. Search the term and you will find GEO, AEO and LLMO guides side by side. If you need one phrase that communicates fastest with buyers, "AI SEO" works. If you need precision in a strategy document, use the definitions above.
Which term is best for local businesses?
None of them changes the local fundamentals. The map pack, reviews and citations still decide local visibility. What the AI layer adds is being the named answer when someone asks an assistant for recommendations in your area. The work is structured answers plus a healthy Google Business Profile.
Is there one official definition for each term?
Only GEO has academic provenance. AEO and LLMO are industry terms defined by whoever is selling them. That is exactly why this page focuses on the work rather than the labels. If two providers define the same term differently, compare their deliverables instead.
If the acronyms have your head spinning, book a free discovery call. One conversation will map what your business actually needs better than three proposals will.