AEO vs GEO vs AI SEO vs SEO: What's the Difference?

Every few months the industry gets a new acronym for getting found in AI answers. First it was AEO, then GEO, and now "AI SEO" and even LLMO show up in job posts and agency pitches. Each new label sounds like one more discipline your team is behind on, and each comparison article seems to draw the lines differently.

The good news: the lines are simpler than the vocabulary suggests. Three of these terms describe the same work today, and the fourth is the ground that work stands on. This guide gives you a one-line definition of each, where each name came from, how they compare side by side, and which one to use.

AEO, GEO, AI SEO and SEO in one line each

• SEO (search engine optimization) makes your pages rank in search engine results so people click through to your site.
• AEO (answer engine optimization) makes your brand the answer an engine gives directly, originally in featured snippets and voice assistants, today inside AI-generated answers.
• GEO (generative engine optimization) makes your brand mentioned and cited in answers that generative AI engines write, such as ChatGPT, Perplexity, Google AI Overviews and AI Mode.
• AI SEO is the name many SEO teams use for the same goal as AEO and GEO: SEO for AI search. (Careful: some people use it for doing SEO with AI tools instead.)

If you only remember one thing: AEO, GEO and AI SEO are three names for one practice, and SEO is the foundation underneath it.

Where each term came from

The terms differ less in what they mean today than in when they were coined, and that history explains most of the confusion.

SEO dates back to the late 1990s, when search engines started ranking pages and businesses started competing for those rankings. Its unit of success has always been a position on a results page and the click that follows.

AEO appeared in the late 2010s, when Google's featured snippets, "People also ask" boxes and voice assistants started answering questions without a click. Winning "position zero" meant getting your text pulled into that single direct answer. The answers were excerpts of existing pages, so AEO was mostly about formatting: concise definitions, question-shaped headings, lists and tables an engine could lift.

GEO was named in a 2023 research paper from Princeton and collaborators, written when large language models started generating answers instead of excerpting them. A generative engine reads several sources, writes a new answer and cites a few of them. GEO studies what makes a source more likely to be used and cited in that synthesized answer.

AI SEO (and its cousin LLMO, large language model optimization) came from practitioners rather than researchers. SEO teams that took on AI search kept the name they already had and added "AI" to it.

Then the answer engines became generative. ChatGPT, Perplexity and Google AI Overviews are answer engines and generative engines at the same time, so the AEO work and the GEO work collapsed into the same job.

AEO vs GEO vs AI SEO vs SEO: side-by-side comparison

AEO vs GEO: what's the difference?

Historically, scope. AEO aimed at a single extracted answer: one snippet, one voice response, one winner. GEO aimed at synthesized answers, where an engine blends several sources and you can win a mention without being the only source. That is why some tool comparisons still describe AEO as the "narrower" discipline.

In practice, that difference is gone. When someone asks ChatGPT for the best CRM for a 20-person startup, the answer is generated, it names several brands and it cites a handful of sources. Optimizing for that answer is AEO and GEO at once. Teams debating whether to "do AEO or GEO" are arguing about vocabulary, not strategy. Our AEO guide covers the term on its own; GEO has its own guide too.

AEO vs SEO: what's the difference?

SEO wins a position in a list and counts on the click. AEO wins a place inside the answer, whether or not anyone clicks afterward. That changes what you measure: rankings and organic sessions on one side; mentions, citations and share of voice across AI engines on the other.

It does not change the foundation. AI engines find content through search indexes and their own crawlers, so a page that can't be crawled, indexed or trusted won't be cited either. AEO builds on SEO; it doesn't replace it.

GEO vs SEO: what's the difference?

The same split applies: SEO optimizes for ranked links, GEO for presence in generated answers. A page can rank first on Google and still be missing from ChatGPT's answer to the same question, and the reverse also happens. The two share infrastructure (crawlability, authority, useful content) but reward different things on top of it, such as citations on trusted third-party sites and answers an engine can extract cleanly.

Whether to invest in one, the other or both depends on your stage and your buyers. Our GEO vs SEO guide walks through that decision company stage by company stage.

AI SEO vs SEO: what's the difference?

When "AI SEO" means SEO for AI search, it is AEO under another name, and the AEO vs SEO comparison above applies. When it means SEO done with AI tools (AI-written briefs, AI keyword clustering, AI content), it is still traditional SEO, just produced faster. The two meanings are often mixed in the same article, so check which one a vendor or agency is selling before you compare offers. LLMO, large language model optimization, belongs to the first group: one more name for AEO.

Which term should you use?

Use one name for your own planning and reporting, and use it consistently. Then, in public content, name the others once so readers searching for any of them, and the AI engines summarizing your page, connect them. A first mention such as "answer engine optimization (AEO), also called generative engine optimization (GEO)" does the job.

Don't let the acronym decide the budget. The work behind every label is the same:

• Keep the SEO foundation healthy. Crawlable, indexable, fast pages with a clear structure.
• Write answers engines can lift. Lead with the direct answer, then the detail. Use question-shaped headings, tables for comparisons and clear definitions.
• Earn mentions where engines look. Reviews, comparisons, communities and media that AI engines cite for your category.
• Measure inside the answers. Track AI visibility, citations and share of voice for the prompts your buyers actually ask, not just rankings and clicks.

That last step is the one most teams skip. Omnia tracks how often ChatGPT, Perplexity, Google AI Overviews, AI Mode and other engines mention and cite your brand, and recommends what to fix. To see where you stand today, run a free AI ranking check.