AEO vs GEO: What the Difference Actually Changes

AEO and GEO are two names for overlapping work: making your content the thing an AI system quotes when it answers a question. AEO, answer engine optimization, is usually applied to the page level, and GEO, generative engine optimization, to the brand level, but no standards body separates them and practitioners use both interchangeably. This piece is for anyone who has been handed a proposal with one of the labels on it and wants to know what is actually being sold. It covers where each term came from, whether the boundary is real, what Google says about optimizing for AI features at all, which work sits under which label, and a two-question test for deciding which one is your constraint right now.

The short version

• There is no agreed definition separating the two. The most common convention puts AEO on the page and GEO on the brand, and that convention is a working habit, not a specification.
• The terms have very different origins. GEO began as a peer-reviewed method with a public benchmark. AEO grew out of industry usage and has no founding document.
• Google's own documentation says there are no additional requirements or special optimizations for its AI features. That statement covers Google's surfaces and says nothing about ChatGPT, Claude, or Perplexity.
• The distinction that changes your work is not definitional, it is diagnostic: is your page unquotable, or is your brand uncorroborated? Those have different fixes.
• If your pages are not indexed, neither label is your problem yet.

What is the difference between AEO and GEO?

In practice, scope. AEO usually names the work of making an individual passage extractable enough to be lifted into an answer. GEO usually names the work of making a brand credible enough to be the one an engine reaches for across many answers. One is about the shape of a paragraph, the other is about what the rest of the web says about you.

That is the convention, and it is worth stating plainly that it is only a convention. Across the sources we reviewed, the two terms are used for the same activity as often as they are distinguished, and vendors draw the line wherever their offer sits. If someone presents you with a hard boundary between the two, they are describing their own taxonomy rather than an industry standard.

	AEO, as commonly used	GEO, as commonly used
Unit of work	A passage on one page	A brand across many sources
Core question	Can this paragraph be lifted out and still answer something?	Do other credible sources describe us the way we describe ourselves?
Where the work happens	On your own site	Mostly off it
How you know it worked	Your passage appears in answers	Your brand appears in answers you have no page for
Typical timeline	Weeks, because you control the page	Months, because you do not control the sources

Where did each term come from?

From different places, and the asymmetry explains most of the confusion. GEO has a founding paper. Pranjal Aggarwal and co-authors published GEO: Generative Engine Optimization, presented at KDD 2024, which formalizes what it calls generative engines and proposes a black-box method for improving a site's visibility inside their responses. Whatever you think of the label, it began as research with a public benchmark rather than as agency vocabulary.

AEO has no equivalent origin. It grew out of the years when featured snippets, voice assistants, and People Also Ask boxes made "the answer" a distinct search result, and the term carried over to AI answers without anyone formalizing it. That is why definitions of AEO vary so widely: there is no document to appeal to.

The practical consequence is one of expectation rather than technique. When someone says GEO, there is a chance they mean the specific method from the paper. When someone says AEO, they almost certainly mean whatever their own practice covers. Asking which is which costs one sentence and saves a lot of misaligned scope.

Is the boundary between them real?

It is real as a division of labor and unreal as a definition. The two kinds of work genuinely differ, and if you flatten them you will spend months on the wrong one. But the labels do not reliably map onto that difference, because different people attach them to different halves.

Our recommendation is to stop arguing about which term applies and describe the work instead. "Making our comparison pages extractable" and "getting third-party sources to describe our category position accurately" are unambiguous. "Doing GEO" is not, and in a proposal it is where the scope goes to hide.

There is one place the terminology does matter: procurement. If you are buying, the label determines what you can hold someone to. A retainer sold as AEO that delivers only reformatted headings has done AEO by one definition. Write the deliverables down instead of the acronym.

What does Google say about optimizing for AI features?

That there is nothing extra to do. Google's documentation on AI features and your website is unusually direct: "There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary." It adds that "the best practices for SEO remain relevant for AI features in Google Search", and closes the door on the two most-sold shortcuts: "You don't need to create new machine readable files, AI text files, or markup to appear in these features. There's also no special schema.org structured data that you need to add."

Read the scope of that statement carefully, because it is where most commentary goes wrong in both directions. It is Google describing Google. It is strong evidence that AI Overviews and AI Mode do not need a separate discipline. It is not evidence about how ChatGPT, Claude, or Perplexity choose sources, because those systems have their own retrieval and their own index, and Google does not speak for them.

So the honest position is split. On Google's surfaces, this is SEO, and treating it as a new discipline mostly sells you work you already needed. Off Google's surfaces, the picture is less documented, which is exactly why the terminology proliferated. Our guide to how AI Overviews select and cite sources covers the Google side in detail.

Which work sits under which label?

Most of it sits under both, which is the practical answer nobody advertises. The table maps the actual tasks against the label they usually get filed under, and against what each task genuinely affects.

The work	Usually filed as	What it actually decides
Question-shaped headings with self-contained answers	AEO	Whether a passage can be lifted at all
Removing context dependence from paragraphs	AEO	Whether a lifted passage still makes sense
Comparison tables and explicit definitions	Both	Whether you are the convenient source for a structured answer
Consistent entity description across your own site	Both	Whether a model can tell what you are
Third-party mentions describing you the same way	GEO	Whether a model is confident enough to name you
Being present in the listicles and directories for your category	GEO	Whether you appear in answers you have no page for
Indexing and crawlability	Neither, usually	Everything. This is the gate before both.

The last row is the one that gets skipped, and it invalidates most AEO and GEO audits performed on young sites. A page a search engine has never fetched cannot be quoted by anything that retrieves from a search index, so a report full of extractability findings about an uncrawled page is describing a problem you do not have yet.

Which one is your actual constraint?

Two questions decide it, and they have to be asked in order. This is the part worth taking from this page.

1. Are your pages indexed and being fetched? Check the URLs you care about in Search Console rather than assuming. If the answer is no, stop here. Neither label applies, and the work is discovery: internal links from pages that are themselves findable, and a crawlable structure.
2. Do you rank for the query but never get quoted? If you rank and are not cited, the problem is usually on the page, and it is extractability. If you are not in the running at all for questions your category owns, and competitors with weaker pages are, the problem is usually off the page, and it is corroboration.

Those two outcomes route to different guides, deliberately. If your passages are the problem, our guide to making a passage quotable sets out the extractability test and how to restructure a section to pass it. If your brand is the problem, our guide to how brands earn AI citations covers the corroboration gate and what genuinely builds it. Working on the second while failing the first is the most common wasted quarter in this area.

Does the terminology change your budget or your team?

Barely, and that is the most useful thing to know before you reorganize anything. The page-level work belongs with whoever writes and edits, because it is editorial structure. The brand-level work belongs with whoever does digital PR and partnerships, because it is other people's pages. Both of those functions already exist in most teams under other names.

What does change is sequencing and expectation. Page work shows results in weeks and is fully in your control. Brand work shows results in months, cannot be forced, and is measured in mentions rather than sessions. Budgeting them on the same timeline is how the second one gets cancelled in month two, just before it would have started to register.

Our guide to AI search optimization covers how these pieces fit together across a full program, including the measurement side, which is where both labels are weakest: neither AEO nor GEO comes with a click-through report, which is exactly why the vendors selling one are worth vetting first; our guide to what to ask an AI visibility tool vendor before you sign covers the questions to ask.

What about AI SEO, LLMO, and the other labels?

They are the same territory with different marketing. AI SEO tends to be used as the umbrella. LLMO, large language model optimization, appears occasionally and means roughly what GEO means. New coinages arrive regularly, and each one arrives with a claim that the previous ones are obsolete. The table below is the working glossary, including which terms resolve to one thing and which do not.

Term	What people usually mean by it	Where it comes from
AEO (answer engine optimization)	Writing and structuring a passage so an engine can extract a direct answer from it	Practitioner coinage with no single traceable origin. Grew out of featured-snippet and voice-answer work.
GEO (generative engine optimization)	Earning inclusion and citation inside an answer a model writes	A defined academic method, introduced in a 2024 research paper with a benchmark attached
AI SEO	The umbrella term for all of it, usually including the classic SEO underneath	Practitioner usage, and the least ambiguous of the informal labels
LLMO (large language model optimization)	Roughly the same territory as GEO, framed around the model rather than the engine	Practitioner shorthand
AIO	Ambiguous. Used for both "AI optimization" and "AI Overviews optimization"	Practitioner shorthand. Avoid it, because it does not resolve to one thing.
ASO	Occasionally "answer search optimization" or "AI search optimization"	Practitioner shorthand, and it collides with App Store Optimization

A simple filter cuts through the list. Ask what a label says you should do that you would not otherwise do. If the answer is "structure answers clearly, be accurate, be described consistently elsewhere, and stay crawlable", the label is a repackaging of established practice, which is not a criticism but is worth knowing before you pay a premium for it. Google's guidance on creating helpful, people-first content remains the underlying standard, and no acronym has replaced it.

When is the distinction worth your attention?

In a few specific situations, and not otherwise:

• When you are buying: the label sets expectations, so replace it with deliverables in the contract. Ask which of the two halves the retainer covers, and what evidence of progress looks like in each.
• When you are assigning work: page-level and brand-level work go to different people with different timelines. Naming the halves keeps them from being merged into one impossible brief.
• When you are reporting: extractability wins and citation wins look different and arrive at different speeds. Reporting them as one number hides which half is working.

Outside those three, the distinction is a taxonomy argument, and taxonomy arguments have never moved a page into an answer. The strongest position is to be able to explain both halves and then talk about the work instead.

The habit worth building: whenever someone uses either acronym, ask whether they mean the page or the brand. That one question resolves almost every disagreement in this area, because almost every disagreement is two people using one word for two different jobs. This week, take your three most important queries, check whether you rank for them and whether an assistant cites you, and write down which of the two halves each result points to. The answer decides where the next quarter goes, and it does not depend on which acronym you prefer.