GEO, AEO and SEO. The definitions keep moving, and there is a reason for that.

The three terms as used

Roughly how the industry uses them, stated fairly before we take issue with it:

Read quickly that looks like a tidy progression. It is not, because the boundaries move depending on who is describing them, and because one of the three has no measurement of its own.

There is no agreed definition

This is not a matter of opinion. The critical survey of generative engine optimization research published by Olivier Martinez in July 2026 reviewed 45 studies covering November 2023 to July 2026. Its finding on vocabulary is direct: terminology, metrics and evidence standards remain heterogeneous.

There is no consensus definition separating these terms in the literature. They are used interchangeably in practice. GEO is doubly ambiguous, because in most of marketing it has meant geographic targeting for years and still does.

The survey's substantive findings matter more than the naming problem:

• GEO is "a stochastic, partially observable pipeline" rather than a ranking task with a lever at the end of it.
• Reported gains depend on the source already being present in context, which is a different thing from being discovered.
• Commercial audits show "substantial run-to-run variability".
• No technique demonstrates stable cross-platform effects on organic discovery.

That last one is the sentence to sit with. After nearly three years and 45 studies, nothing has been shown to reliably work across platforms. That is the honest state of the field being sold as a premium service.

Why they cannot settle

Terminology fractures when measurement is broken. Everybody names a slightly different version of the thing they think they are optimising, because nothing forces the names to converge.

In SEO, an argument about definitions can be settled. Two people disagreeing about whether a change worked can open Search Console and look at the same numbers. Imperfect, but shared.

In AI search there is no equivalent. Citation counts, visibility scores and share of voice are all built on systems that return different answers to the same question. Run a prompt twice and you can get two different lists. With no stable measurement, no definition can be tested, so vocabulary drifts toward whatever is easiest to sell.

The naming confusion is not a communication problem that better articles will fix. It is a symptom of an unsolved measurement problem.

This is also why we treat run-to-run variance as the first thing to establish rather than a footnote. Any claim about AI visibility that does not account for the same prompt returning different answers is describing noise with confidence.

What happened to AEO

AEO has largely been absorbed into GEO. Some agencies still sell it as distinct. The underlying work is now effectively the same.

The term made sense when answer engines meant featured snippets and voice assistants, which were a specific and separable target. Once generative systems became the dominant way answers get assembled, the distinction stopped describing anything different in practice.

If a proposal separates AEO from GEO as two line items, the question is what work appears under one that does not appear under the other. In most cases nothing does, and the separation exists to make a scope look larger than it is.

How they actually relate

The relationship worth understanding is not three disciplines side by side. It is one foundation with two surfaces on top.

Everything downstream depends on the same four things. Can the page be reached and retrieved. Is the business and the offer clearly stated. Is there evidence for the claims. Do independent sources corroborate any of it.

Those are the same requirements a search engine has had for years. What changed is what gets returned. A search engine hands back a list of pages and lets the reader choose. A generative engine assembles an answer and names a shortlist, so being retrievable is necessary but no longer sufficient. You also have to be worth naming, which is mostly a question of evidence.

The question to ask a vendor

One question separates a real distinction from a naming exercise:

What measurement changes when this work succeeds, and what is the baseline?

• For SEO, there is a clean answer. Impressions, clicks and positions for a defined query set, from Search Console, compared against a dated before period.
• For GEO, an honest answer is a fixed prompt set, run repeatedly, recorded with dates, reporting variance alongside the result.
• For AEO as a separate line item, there usually is no answer, because there is no measurement that distinguishes it from the GEO one.

If the response is a proprietary visibility score with no stated method, that is the measurement problem the whole naming confusion grows out of, sold back to you as a number.

Our own answer to that question is a fixed prompt set with the variance reported alongside the result. If you are still deciding whether any of this applies to you yet, start with whether your buyers use AI to choose at all.

Limits

• The Martinez survey is one review, published July 2026, and reviews are shaped by which studies they include. Its findings on heterogeneous terminology and unstable effects match what we see, which is why we lean on it, but it is a single source.
• "No demonstrated stable cross-platform effect" does not mean nothing works. It means nothing has been shown to work reliably across platforms in published research. Those are different claims and the distinction cuts both ways.
• This is a fast-moving field. Anything here describes September 2026.
• We have a commercial interest in this argument. We sell SEO and AI visibility work, and our position that GEO is not a separate premium service is a position that suits how we prefer to work. Weigh it accordingly.

The vocabulary will probably settle eventually. It will settle when the measurement does, and not before.