Explainer
What is the difference between SEO, AEO, GEO, and LLMO?
Four labels, one underlying job. SEO earns a position in Google’s results list. AEO earns the direct answer to a specific question, the kind that shows up in a featured snippet. GEO earns a mention inside an answer a generative system composes, in ChatGPT, Gemini, or Perplexity. LLMO describes the same work from the language model’s side rather than the reader’s. They overlap heavily, and all four rest on the same technical foundation.
SEO: competing for a place in the list
Search engine optimization earns a website a higher position in Google’s organic results. Someone searches “office chair,” and SEO decides which site sits at the top of that list of blue links. Load speed, technical structure, relevant content, and authority from other sites linking to you still decide the outcome.
What SEO no longer covers on its own
Google now shows an AI Overview or an AI Mode answer above the classic list for a growing share of searches. A strong position in that list no longer guarantees the most visibility. The classic foundation still matters: no AI system can draw on a site it cannot crawl or parse.
AEO: competing for the answer itself
Answer engine optimization targets the answer, not the position around it. SEO asks whether you appear in the list. AEO asks whether you are the answer.
Featured snippets and AI answer boxes
Search “how much does a window screen cost,” and Google sometimes shows a short box at the top with a price range, lifted straight from a page. That box is a featured snippet, the most familiar form of AEO. Pose the question as a subheading and answer it in the first sentence below, and you give yourself the best shot at it.
GEO: competing for a mention inside a composed answer
Generative engine optimization goes a step past AEO. Where AEO still assumes a search engine’s answer box, GEO concerns a mention inside an answer the system writes from scratch. Ask ChatGPT which agency can reactivate a dormant customer database, and GEO decides whether your company appears somewhere in that answer, with no click on your site involved.
How ChatGPT, Gemini, and Perplexity pick sources
These systems do not crawl the way Google’s classic crawler does. They combine several sources into one answer and favor content that confirms a fact quickly and clearly: a concrete number, a clean definition, a page that gets to the point. A strong backlink profile still helps, though it counts for less here than in classic SEO. Clarity and verifiability count for more.
LLMO: the same work, described from the model’s side
LLMO stands for large language model optimization: structuring content and technical setup so language models can read, understand, and cite it. It overlaps almost entirely with GEO. Someone who says LLMO usually means the same effort as someone who says GEO, framed from the model’s mechanics rather than from the answer a reader sees.
Why the experts disagree about this label
As of early 2026, no settled definition separates SEO, AEO, GEO, and LLMO. Some sources treat LLMO as the umbrella with AEO and GEO beneath it. Others use LLMO as a synonym for GEO, or drop the label entirely and let GEO cover everything. A page that presents this as a tidy hierarchy is simplifying. While the field disagrees with itself, the honest conclusion is that the terms overlap and the underlying practice is what counts.
Which term applies to your business?
You rarely pick one row from this table. It shows which label belongs to which question.
| Your situation | Relevant term |
|---|---|
| You want a higher position in Google’s classic results list | SEO |
| You want your content to become the featured snippet for a specific query | AEO |
| You want ChatGPT, Gemini, or Perplexity to mention you in an answer | GEO |
| You want every language model to read and cite your content correctly | LLMO |
Most businesses work on all four at once rather than one row in isolation. That is exactly why the line between the terms is blurrier in practice than the table suggests.
Why these are not four separate projects
Google’s own guide to AI search optimization is unusually direct about this: optimizing for generative AI features in Search is still SEO. Google states that no separate technical approach is required, no llms.txt file, no content chopped into blocks, and no distinct writing style for AI. What it takes is a technically sound site with clear, factually grounded content, the same foundation classic SEO has run on for years.
That matches how we work. Our GEO and AEO explainer shows how the three converge into one approach rather than three tracks, and our AI-SEO service builds on it: a technical base both search engines and AI systems can read, with content that earns a Google position and a mention in an AI answer.
Want to know what to actually do about it? Here is AI search optimization in six steps.
Frequently asked questions
Is GEO the same as AEO?+
No, though they sit close together. AEO targets a direct answer to one specific question, such as a featured snippet. GEO targets a mention by a generative AI system inside a composed answer. Most businesses work on both at once.
Is LLMO a different field from GEO?+
Not meaningfully. The industry has not settled where the boundary falls. AEO and LLMO get used interchangeably, while GEO is the most common label for the same work. Focus on the practice rather than the label.
Should I drop SEO in favor of GEO?+
No. A healthy classic SEO foundation, meaning load speed, technical structure, and authority, remains the precondition. AEO and GEO build on it rather than replace it.
Which term should I use with my agency?+
Whichever one they can explain without jargon. The label matters less than whether they can show you where your business currently appears in AI answers and what changes that.
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