AEO, GEO, and SEO: what the terms actually mean

The terminology around this has got messy, largely because a lot of people had an incentive to name a new discipline they could sell. It is worth being precise about what each term means, because the distinctions that matter are not the ones the acronyms suggest.

The three terms

SEO: search engine optimisation. Making your pages appear in the results a search engine returns. Forty years of accumulated practice, well documented, well understood.

AEO: answer engine optimisation. Making your content the source that an AI-generated answer draws on and cites, whether that answer appears in Google's AI Overviews, ChatGPT, Perplexity, Claude, or Gemini.

GEO: generative engine optimisation. The same thing as AEO. The two terms emerged around the same time from different sources and have been used interchangeably ever since. Some practitioners argue GEO applies specifically to generative systems while AEO also covers featured snippets and voice assistants, but that distinction is not applied consistently enough to be useful.

If you are trying to decide which one to hire for, that is the wrong question. They describe the same work.

The distinction that actually matters

Forget the acronyms. There are two genuinely different things happening, and separating them will tell you more than any definition.

Retrieval. The AI system searches the live web, reads what it finds, and produces an answer from those sources. Google's AI Overviews work this way. So does Perplexity, and so does ChatGPT or Claude when browsing is enabled.

Training. The model answers from what it learned during training, with no live lookup. This is what happens when you ask ChatGPT a question with browsing off.

These respond to completely different inputs on completely different timescales.

Retrieval responds to what your site looks like right now. Improve your structure, your crawlability, your content, and retrieval-based systems can reflect that within weeks. This is the surface your work actually influences.

Training reflects what was on the web when the model was trained, filtered through whatever the training process emphasised. You cannot optimise for it in any direct sense, and changes to your site will not show up until a future training run, if ever, for most companies.

Almost every claim you will read about "optimising for ChatGPT" fails to make this distinction, which is why so much of the advice is untestable.

What actually influences citation

For the retrieval side, which is the part you can affect, four things do most of the work.

Technical accessibility. If your content is not in the initial HTML, requires JavaScript to render, or sits behind a wall that blocks AI crawlers, you are not a candidate. This sounds basic. It disqualifies a surprising number of otherwise well-built sites.

Structure that isolates answers. AI systems extract passages, not pages. A self-contained, direct answer near the top of a page is far more extractable than the same information distributed across a thousand words of narrative build-up. Clear headings that describe rather than tease. Questions answered where they are asked.

Entity clarity. These systems build a model of who you are, what you do, and what you are authoritative about. That model is assembled from consistent signals across the web: your site, your structured data, your profiles, your mentions elsewhere. Inconsistency weakens it. If your title differs across your website, LinkedIn, and your conference bios, you are making the system less certain about you.

Information that cannot be synthesised. Original data, specific results, named methodology, first-hand experience. A model can produce a competent general answer from the hundred articles that already exist. It cannot produce your numbers without citing you.

What you should stop worrying about

Some of what is being sold under these acronyms is not supported by anything.

Keyword density and phrasing tricks aimed at language models. These systems work on meaning, not string matching.

Wholesale rewriting of your existing content into a question-and-answer format. Structure helps. Mechanically converting every page into an FAQ does not, and it usually makes the content worse to read for the humans who do still arrive.

Paying for inclusion in AI answers. That is not a thing that currently exists in any legitimate form.

What this means practically

You do not need a separate AEO team, budget line, or vendor. You need three adjustments to work you are probably already doing:

Measure a different outcome. Rankings and sessions do not tell you whether you are being cited. That requires checking deliberately, under controlled conditions, on a fixed set of prompts, repeated over time.

Prioritise differently. Technical accessibility and original material move ahead of publishing volume, which for most teams is a significant reordering.

Be consistent about who you are. Entity signals are cheap to fix and most companies have never audited them.

The acronym you use for this does not matter. Whether you have measured where you currently stand does.

This article is part of the SEO in the AI Era: The Complete Guide guide.