LLMO vs GEO vs AEO: what the terms actually mean

Four acronyms now describe roughly the same job: getting your brand named by AI. AEO, GEO, LLMO, AI SEO. The labels cause more confusion than they resolve, so here is what each actually means, which one has real backing, and why the most authoritative voice in search says the distinction barely matters.

Every few months the industry mints a new acronym for the same anxiety: my brand is invisible in AI answers, and I want to fix it. AEO, GEO, LLMO, AI SEO, AIO. They are not five different disciplines. They are five labels circling one shift. Here is how to tell them apart, and why you should not lose sleep over which one you use.

What each term actually means

• AEO - Answer Engine Optimization. The oldest of the four. It predates the current AI wave and originally meant optimizing to be the direct answer: featured snippets, "People Also Ask", voice results, answer boxes. It is about being the answer, not just a link.
• GEO - Generative Engine Optimization. Being cited inside AI-generated answers, from ChatGPT and Perplexity to Google's AI Overviews. This is the term with the strongest pedigree, which matters below.
• LLMO - Large Language Model Optimization. The broadest and fuzziest. It covers how a brand is represented in model outputs generally, including what a model recalls from its training data before it retrieves anything from the live web.
• AI SEO / AIO. Umbrella labels, mostly used in marketing. They rarely mean anything more precise than "SEO, but for AI".

Curious how AI engines describe your brand right now? Get a free visibility audit and see where you stand across ChatGPT, Gemini and Perplexity.

Which term has real backing

Only one of these came out of peer-reviewed research. GEO originates from a Princeton-led paper, "GEO: Generative Engine Optimization," published at the ACM SIGKDD conference in 2024. That gives it a credibility the marketing-coined terms lack, and it is why most tool vendors have standardised on GEO.

The paper is also useful for a more practical reason: it actually tested what moves the needle. Its headline finding was that well-chosen tactics could lift a source's visibility in generative answers by up to 40%, and that the biggest gains came from adding cited sources, quotations and statistics. Notably, keyword stuffing and simply adopting an authoritative tone did nothing, or hurt. That is a real, evidence-based result, not a vendor claim.

"The terms are converging on one playbook. The differences are emphasis, not method."

The distinction that actually matters

Strip away the branding and there is one genuine conceptual split worth understanding, and it is not between AEO and GEO. It is between two ways a model can mention your brand:

Retrieval - the model searches the live web, finds sources, and cites them. This is what GEO and AEO mostly target, and what you can influence relatively quickly with good, citable content.

Recall - the model answers from what it absorbed during training, with no live search. This is the LLMO end of the spectrum, and it moves slowly, shaped over months by how widely and consistently your brand is described across the web.

Most real-world AI answers now involve retrieval, which is why the retrieval-focused tactics get the attention. But the recall layer is why consistent, widespread, accurate presence still matters even when no citation appears.

Why Google says it is all still SEO

Here is the deflating, clarifying truth. In guidance published around May 2026, Google stated there is no separate AI-search strategy: optimizing for its AI features, including AI Overviews and AI Mode, is the same as optimizing for Search. No AI-specific schema, no special content chunking, no separate rewrite.

That does not make the acronyms useless - they usefully name a shift in where you need to show up. But it should calm anyone worried they need a whole new discipline. The fundamentals that earn AI citations, being clearly defined, well-structured, credibly sourced and genuinely authoritative, are the same fundamentals that have always earned good search visibility.

The takeaway

Use whichever term your audience uses. GEO has the academic backing and vendor adoption, AEO has history, LLMO captures the training-recall angle, and Google will tell you it is all still SEO. What does not change underneath the labels is the work: make your brand the clear, corroborated, citable source on the questions that matter, and measure whether the engines actually name you. The acronym is a wrapper. The outcome is the point.

Related: AEO vs SEO, and why strong SEO doesn't guarantee AI visibility →