SEO vs AEO vs GEO: What Each One Actually Means

Where each term came from

SEO is twenty-five years old and needs no introduction: make pages a search engine can crawl, index and rank, and compete for a position in a list the user then clicks. The unit of success is a ranking, and the payoff is a visit.

AEO — answer engine optimisation — predates the current generative engines. It grew out of featured snippets and voice assistants, where the engine returned a single answer and the entire job was to be that answer. That constraint shaped the tactics: answer the question directly in the first lines, structure content so a machine can lift a passage cleanly, use question-shaped headings. Those tactics survived the transition and are still the core of the on-page work today.

GEO — generative engine optimisation — has an unusually precise origin for a marketing term. It was coined in a November 2023 arXiv paper by researchers from Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi, later presented at KDD 2024. The paper's premise is the thing that separates GEO from AEO: a generative engine composes an answer from several retrieved sources and cites a handful of them, so the goal is not to be the single answer but to be among the cited. That study also produced the only peer-reviewed effect sizes in this field — adding statistics, quotations and cited sources lifted visibility by up to 41% on position-adjusted word count, while keyword stuffing showed little to no improvement.

You will also meet AIO, LLMO and "AI search optimisation". These are umbrella terms with no agreed technical definition. Read the deliverables, not the acronym.

Side by side

The one place they genuinely diverge: measurement

Almost all of the on-page work is shared. Crawlability, answer-first structure, entity consistency, credible sourcing — these serve all three, which is why "AEO vs GEO" is a weak basis for two separate invoices. The real divergence is what counts as evidence.

In SEO you can verify a claim yourself: open a private window, type the keyword, look at position four. AEO was almost as checkable — the snippet was there or it was not. GEO broke that. Ask a generative engine the same buyer question twice in fresh sessions and the brands it names routinely differ. In our own seven-engine test, the average overlap between the source sets two engines returned for the same question was 0.091 in English — roughly one source in ten. That is why a GEO result is only meaningful as a frequency across repeated runs, reported per engine, and why a single screenshot proves nothing in a way that a snippet screenshot did.

Everything else follows from that one property. It is the reason serious GEO work archives raw answers, locks a query set before starting, and refuses to blend engines into one score.

Do you need all three?

You need the underlying work, once. Split by outcome rather than by acronym: if buyers still click links to reach you, classic SEO earns those visits and remains the foundation — generative engines retrieve from the same indexes, so a page that cannot be crawled or indexed cannot be cited either. If buyers increasingly act on the answer without clicking, the AEO/GEO layer decides whether you are in that answer at all. Most businesses need both, and the split of effort is a question about your buyers, not about terminology. We work through that decision concretely in GEO vs SEO in 2026 and on the decision guide.

How to spot a repackaged retainer

Three questions do it. Ask which deliverables differ between their AEO and GEO offerings — if the answer is a list of the same items with different labels, it is one service. Ask how each is measured — a vendor who cannot describe run counts and per-engine reporting has not built the GEO half. Ask what they would stop doing if you bought only one — a genuine distinction survives that question; a marketing one does not.

The longer procurement version is our twelve-question evidence checklist, and what belongs in a contract instead of a promise is in whether an agency can guarantee results. If you want to see where you currently stand across engines before deciding any of this, run a free AI visibility audit.

Frequently Asked Questions

What is the difference between SEO, AEO and GEO?

SEO earns a position in a list of links that users click. AEO — answer engine optimisation — comes from the featured-snippet and voice era and aims to be the single answer an engine returns. GEO — generative engine optimisation, from a 2023 paper presented at KDD 2024 — aims to be among the sources cited inside an answer synthesised from several pages. The on-page work overlaps almost entirely; the substantive difference is that GEO results are unstable run to run and therefore have to be measured as frequencies across repeated probes rather than checked once.

Is AEO the same as GEO?

Not historically, but close enough operationally that they should not be sold as two services. AEO assumes one answer and one source; GEO assumes an answer composed from several with citations attached. The tactics AEO produced — direct answers in the first lines, question-shaped headings, extractable passages — are still the backbone of GEO on-page work. If a vendor charges separately for both, ask which deliverables actually differ.

Is SEO dead now that AI answers exist?

No, and the mechanism is the reason: generative engines retrieve from search indexes. A page that cannot be crawled or indexed cannot be cited. What has changed is that ranking well no longer guarantees being in the answer, and being cited in the answer no longer requires ranking first — the two channels have partially decoupled, so covering only one leaves the other unattended.