AEO vs GEO vs SEO: Three Names, One Job

Quick verdict

TL;DR

• Generative engine optimization was coined in an academic paper, GEO: Generative Engine Optimization by Aggarwal and colleagues, posted to arXiv in November 2023 and presented at KDD 2024 in Barcelona. It is the only one of the three terms with a formal definition and a benchmark.
• That paper introduced GEO-bench, a benchmark of 10,000 queries across 25 domains, and tested nine content strategies.
• Its headline finding of up to 40% visibility improvement is a maximum, not an average. The three strongest methods produced roughly 30% to 40% relative improvement on the paper's own visibility metric.
• The winning methods were citing sources, adding quotations and adding statistics. Those are not new tactics.
• Keyword stuffing scored about 8% below the unmodified baseline in the paper's tests, and around 10% below in its Perplexity validation. The classic search-era abuse tactic measurably backfires here.

If you want the strategy rather than the vocabulary, our guide to answer engine optimization covers how the work actually splits and what to fund.

What is the difference between SEO, AEO and GEO?

AEO vs GEO vs SEO comes down to scope. All three are about being found. They differ in what "found" means.

• SEO aims at a ranked link on a results page. Success is a position and a click.
• AEO aims at your text being extracted as the answer, in a featured snippet or an AI summary. Success is a quoted passage.
• GEO aims at your brand and content appearing across AI-generated responses generally. Success is a citation or a mention.

Two plain-English terms worth pinning down, because they are used loosely:

• An answer engine is any system that returns a direct answer rather than a list of links. A featured snippet is one. So is an AI summary.
• A generative engine is a system that writes an original response by pulling from sources, such as ChatGPT, Perplexity or Google's AI features. The GEO paper defines it as a combination of a generative model and a search engine.

The tactics overlap almost completely. Be crawlable. Answer the question clearly and early. Cite your claims. Use structure a machine can parse. Those four sentences serve all three.

Where did each term come from?

AEO vs GEO vs SEO have very different pedigrees. Two of the three have traceable origins; one does not.

SEO dates to the late 1990s and needs no defence. It is a settled term with decades of practice behind it.

GEO has a paper. GEO: Generative Engine Optimization by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande was posted to arXiv in November 2023 and presented at KDD 2024, the ACM's flagship data mining conference, in Barcelona that August. It formally defined generative engines, introduced a benchmark, and ran controlled experiments.

A small correction worth making: this is widely called "the Princeton study". It is more accurately a collaboration. The lead author was at IIT Delhi and the Princeton affiliation comes from a co-author. Calling it the Princeton paper is not wrong, but it is not the whole picture, and a term's credibility should not rest on a misremembered affiliation.

AEO has no equivalent. No paper coined it, no benchmark measures it, no standards body defines it. It emerged from marketing practice, which is not disqualifying, but it does mean that when two vendors describe AEO differently, neither is wrong. There is nothing to be wrong about.

One term with a peer-reviewed definition, one with thirty years of practice, one with neither. That is the honest state of the vocabulary in 2026.

What did the GEO research actually measure?

Only one term in the AEO vs GEO vs SEO trio has been tested this way: nine content strategies, across 10,000 queries, and the results are less exotic than the term suggests.

The paper introduced GEO-bench, a benchmark of 10,000 queries spanning 25 domains, split into training, validation and test sets. It then tested nine ways of modifying content and measured the effect on visibility inside generated answers, using a metric that accounts for both how much of your content appears and where it appears in the response.

Up to 40%: the headline visibility improvement from the founding GEO paper. It is a maximum, not an average (Aggarwal et al., KDD 2024)

That distinction matters and is routinely dropped. The three strongest methods produced roughly 30% to 40% relative improvement over an unoptimised baseline. That is a real result. It is not a promise that any change lifts visibility 40%.

What worked:

What did not work:

Read those two tables together. The founding research on this supposedly new discipline found that the winning moves are citing your sources, quoting authorities, using real numbers and writing clearly. The losing move is the oldest abuse tactic in search.

The paper also found that effectiveness varied by domain, which is why a single universal checklist is a poor substitute for testing on your own material.

Do the three need separate budgets?

No, for almost every company. In the AEO vs GEO vs SEO comparison, one programme covers all three because the work is largely the same work.

One row is genuinely distinct, and it is the off-page one. Being present on the review sites, directories and communities that AI assistants pull from is work that ordinary SEO does not automatically do. That is the only part of this that plausibly justifies a separate line item.

Where a separate AEO or GEO retainer is the weaker choice: for most companies under 250 people, buying three retainers means paying three times for crawlability, content quality and structure. If a proposal lists AEO and GEO as separate services, ask which specific activities appear in one and not the others. If the honest answer is only the off-page row above, you are being sold a vocabulary rather than a service.

What does Google say about the terms?

That for Google Search, AEO vs GEO vs SEO is not a real distinction. Google's guide to optimizing for generative AI features addresses AEO and GEO by name and states that from Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and is therefore still SEO.

That is Google's position on Google's own surfaces. It is not a statement about ChatGPT or Perplexity, which retrieve differently and are not covered by Google's documentation at all. The distinction matters and is covered in our guide to ranking in AI Overviews.

So the accurate summary is narrower than either camp claims. For Google, the three terms collapse into one. For assistants outside Google, there is genuinely different work to do, and it is mostly off your own website.

Choose SEO if, choose AEO if, choose GEO if

Use the word SEO if you are talking to a board, a CFO or anyone outside marketing. It is understood, it has thirty years of shared meaning, and inventing vocabulary in a budget meeting costs you credibility.

Use the word AEO if your specific goal is being extracted as a direct answer, in featured snippets or AI summaries, and you want to name that narrower job. Accept that the term is informal and that your vendor may define it differently from you. Agree the definition in writing.

Use the word GEO if you are discussing visibility across AI-generated responses generally, or citing the research. It is the one term with a formal definition, so it is the safest of the three to use precisely.

Use none of them if what you actually need is basic technical fixes and better content. A site that is not crawlable does not have an AEO problem.

Buy one programme, not three, unless the proposal can name activities in each that appear in neither of the others.

What should you actually measure?

Three things, and none requires you to settle the vocabulary first.

Rankings and clicks, from Google Search Console, which is first-party and free. This covers the SEO scope.

Presence in Google's AI features, using Search Console's Generative AI performance report. This is the only first-party data Google publishes on that surface.

Citations in assistants, by running a fixed set of your buyers' real questions through ChatGPT, Perplexity and Gemini on a schedule and recording which brands and domains appear. This is a measurement you build rather than a metric you buy, and it is the only reliable way to see the surface Google does not report on.

If a vendor proposes an "AI visibility score" without explaining how it is calculated, treat it the way you would treat any unexplained composite number. The method matters more than the figure.

What do most teams get wrong?

Paying twice for the same work. The three-acronym split is where it happens. The most common and most expensive mistake, and the reason for this article.

Quoting the 40% figure as an average. It is a maximum from a specific benchmark using a specific metric. Repeating it as a general expectation is how a real research finding becomes a sales claim.

Assuming AEO has a fixed definition. It does not. If it appears in a contract, define it in the contract.

Reaching for keyword stuffing under a new name. The GEO paper measured it performing below the unmodified baseline. Whatever you call the discipline, that tactic is worse than doing nothing.

Skipping the off-page work. It is the one genuinely distinct activity in the whole comparison, and it is the one most likely to be dropped because it does not happen on your own site.

Arguing about vocabulary instead of measuring surfaces. Nobody who searches for you cares what you call it.

How does Euracle scope this work?

Euracle treats AEO vs GEO vs SEO as one programme with named surfaces, not three retainers with three names.

The Eureka Method, Euracle's discovery sprint, runs four phases.

Discover lists the surfaces that actually matter for the client's buyers, which is usually Google results, Google's AI features and two or three assistants, and measures the current position on each.

Design allocates effort by surface rather than by acronym, which makes the overlap visible instead of billable.

Deploy ships the on-page work once and the off-page work separately, because only the second is genuinely additive.

Scale re-runs the assistant prompt set monthly, since that surface moves fastest and reports nothing back to you on its own.

Two structural commitments come from how Euracle is set up. Senior practitioners only: the people in the pitch do the work. And one contract across six disciplines, which is directly relevant here, because splitting one job into three retainers is a commercial structure rather than a technical necessity.

If you want the surfaces named and measured before anyone quotes you a retainer, that is Euracle's AEO and GEO service. The duplicate-retainer problem shows up most often at B2B SaaS companies, where separate content and demand-generation budgets make it easy to buy the same work twice.

The keyword side of this sits in our B2B keyword research guide, which covers how AI answers change which terms are worth targeting at all.

Conclusion

You can now treat AEO vs GEO vs SEO as a scoping question rather than a vocabulary question. Ask what surfaces your buyers use, measure your position on each, and fund the work once. Cite your claims, use real numbers and write clearly, because those are the methods the founding research actually measured. Skip keyword stuffing under any name, since it performed worse than doing nothing. And if a proposal lists AEO and GEO as separate services, ask which activities appear in one and not the others before agreeing to pay twice. If you want the surfaces named and measured first, talk to Euracle about AEO and GEO.

Sources

1. Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., and Deshpande, A. GEO: Generative Engine Optimization. arXiv:2311.09735, November 2023; published in KDD '24, Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, 25 to 29 August 2024. DOI 10.1145/3637528.3671900. https://arxiv.org/abs/2311.09735
2. Google Search Central, Optimizing your website for generative AI features on Google Search, last updated 10 July 2026. States that AEO and GEO, for Google Search, are still SEO. https://developers.google.com/search/docs/fundamentals/ai-optimization-guide
3. Google Search Central, AI Features and Your Website, on eligibility and the Generative AI performance report. https://developers.google.com/search/docs/appearance/ai-features
4. Method-level results from the GEO paper, including the 30% to 40% relative improvement for the strongest methods and keyword stuffing performing below baseline.

Written by

Devanshu Takkar

AI-Native Product Manager + GTM Engineer