AEO vs GEO: are they the same thing?

The short answer

Treat them as the same practice, because in operational terms they are, and nobody has produced a definition that holds up under checking.

A July 2026 academic survey of the whole field states plainly that “terminology, metrics, and evidence standards remain heterogeneous.” Google states that AEO and GEO are both part of SEO. Neither of those is a vendor position.

So when someone tells you AEO and GEO are different disciplines needing separate budgets, the right response is a question: which definition are you using, and where is it from?

Key takeaways

• GEO has a paper. Aggarwal and colleagues introduced the term in November 2023, published at KDD 2024, with a formal framework and the public GEO-bench benchmark.
• AEO has no canonical source. It is an industry coinage, which is not a criticism, but it means there is no definition to point at.
• The 2026 academic survey says terminology remains heterogeneous. Nobody has settled this, and a vendor claiming otherwise is not citing anything.
• Google treats both as part of SEO. Its May 2026 guidance is explicit, and AI Overviews run on core Search ranking systems with no separate index.
• The work does not differ. Access, extractability, evidence and off-site authority, whichever label is on the invoice.

A note on where this comes from. We run organic for more than 250 enterprises and track over 10 million prompts across every major engine. What follows is shaped by that, and by the client reviews we sit in weekly. Also by calls with buyers quoted separately for AEO and GEO by one firm.

What is generative engine optimization, actually?

It has a definition, from the paper that introduced it.

Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan and Deshpande submitted “GEO: Generative Engine Optimization” on 16 November 2023, and it was published at KDD 2024. The paper describes GEO as a framework “to aid content creators in improving their content visibility in generative engine responses,” built as a flexible black-box optimization approach with defined visibility metrics.

It also created GEO-bench, a public benchmark of user queries across multiple domains with the web sources needed to answer them, and reported visibility improvements of up to 40% in generative engine responses, while noting that effectiveness varied by domain.

Two things worth holding onto. First, the figures are from 2023 and the engines have changed largely since, so treat them as the origin of the term rather than as current performance data. Second, and more usefully: this is what a defined term looks like. A source, a method, a benchmark others can run.

A July 2026 survey of the field by Olivier Martinez carries the definition forward, describing GEO as work that “seeks to increase content’s presence, likelihood of citation, or influence in answers produced by generative engines,” and characterising it as “not a single ranking task but a stochastic, partially observable pipeline.”

What is answer engine optimization, actually?

This is where it gets thinner, and it is worth being straightforward about it.

AEO has no founding paper and no canonical definition. The term grew out of the SEO industry, at first around featured snippets and voice assistants, and broadened to cover AI answers as those arrived. Different practitioners define it differently, and none of those definitions traces to a common source.

If you would rather skip the vocabulary argument entirely, book a growth audit and we will show you what is actually limiting your presence.

That is not a criticism of the term. Plenty of useful vocabulary emerges from practice rather than from research. But it has a practical consequence: when two people disagree about whether AEO and GEO differ, there is no authority to appeal to. They are comparing one term with a paper against one term with a consensus that does not exist.

The 2026 survey is explicit about the state of things, noting that “terminology, metrics, and evidence standards remain heterogeneous” across the field. It focuses on GEO throughout and does not treat AEO as a separate discipline requiring its own definition.

AEO vs GEO at a glance

The last row is the practical one. GEO’s formal definition is narrower than everyday usage, and AEO has nothing to be narrower or broader than.

Is there any real difference in the work?

No, and this is the part that matters more than the etymology.

Whichever word is on the invoice, the sequence is the same:

Access. Can the engine fetch and render your page. Every AI company runs a search crawler and a separate training crawler, and blocking the wrong one removes you from answers. Retrieval failures caused more than 70% of chatbot errors in a Stanford-led review across 2,100 questions in May 2026.

Extractability. Can a single passage be lifted without rewriting. Zhang, He and Yao measured 21,143 citations in April 2026 and found absorbed pages are longer, more structured, and richer in definitions, numerical facts, comparisons and procedural steps.

Evidence. Does the page contain sourced numbers and stated methods rather than general claims.

Off-site authority. Do the sources engines favour mention you. Muck Rack’s analysis of more than 25 million cited links found earned media accounted for 84% of AI citations against 0.3% for paid. Muck Rack sells PR software, so read it as an interested party with a large dataset.

None of those four steps changes depending on which acronym you use. That is the operational answer, and it is why we treat the difference as vocabulary rather than strategy.

Where does each term actually fall short?

Generative engine tuning falls short on scope. Its formal definition concerns presence inside generative responses. In practice people use it to cover technical retrievability, content and digital PR, which is much broader than the paper describes. The term has outgrown its definition.

Answer engine tuning falls short on precision. With no canonical source, it means whatever the speaker needs it to mean. That makes it useful in call and useless in a contract, which matters when you are comparing two proposals using the same word for different scopes.

“AI search optimisation” and “LLM SEO” fall short the same way, and for the same reason. Both are descriptive phrases rather than defined terms.

And our own vocabulary falls short too. Pepper uses GEO as the umbrella term across our platform and our writing. That is a choice for consistency, not a claim that the paper’s definition covers all we do. We think naming that is more useful than pretending the terminology is settled.

What nobody should promise you

That AEO and GEO require separate programmes. Google states both are part of SEO, and the 2026 academic survey says terminology remains heterogeneous. Nobody has a definition supporting the split.

A definition of AEO with a source behind it. If someone offers one, ask where it is from. We looked and could not find a canonical origin.

Guaranteed citations under either label. Google advises against providers guaranteeing rankings, because third parties cannot access internal ranking systems.

That the 40% figure from the original paper describes today. It was measured in 2023 on engines that have changed largely. It established the term, not current performance.

How to evaluate anyone selling you a distinction

I would ask one question and listen carefully to the shape of the answer, because it separates a considered position from a sales line in about thirty seconds.

“Which definition of AEO are you using, and where does it come from?”

A good answer acknowledges there is no canonical source, explains how the speaker uses the term, and describes what they do rather than what it is called. A weak answer asserts a difference and moves on, or produces a definitions table with no citation under it.

Google’s May 2026 guidance is the anchor. Google states that AEO and GEO are part of SEO, and that AI Overviews and AI Mode run on core Search ranking systems with no separate AI index. That is correct for Google, and Google is one engine, since ChatGPT and Perplexity retrieve and cite differently. Hold both: the fundamentals are shared across every label, and the per-engine differences are real but have nothing to do with which acronym you use.

What the split actually costs

Three concrete ways an oversold distinction shows up in a budget. Being quoted twice for one scope, with an AEO line and a GEO line covering the same activities. Buying two tools, when platforms marketed under each label cover substantially the same vendor set, as our comparison of AEO tools and GEO tools shows. And splitting a team in two, which is the expensive version, covered in our guide to adding GEO to an existing SEO scope.

If you want the practical version rather than the definitional one, book a growth audit and we will show you what is actually limiting your presence, whatever it is called.

Score the proposal, not the vocabulary

Judge what a firm does, not what they call it.

Those weights sum to 100. Sourcing standards dominate because in a category with no settled vocabulary, how a vendor handles evidence about their own service is the cheapest signal you have about everything else.

The live test

Take 30 real commercial questions from your category, written the way a buyer types them. Four worked examples: “what is the difference between AEO and GEO”, “do we need an AEO agency or a GEO agency”, “best tool for answer engine optimization”, “how do we get cited by ChatGPT in our category”. Run each across ChatGPT, Perplexity and Google AI Mode, more than once, because engines are probabilistic and one run establishes nothing.

Then look at what comes back and ask five things. Where do we appear and where do we not. Which competitors appear instead, reliably. Which sources influence those answers, sorted by frequency. Why are those sources winning. What would change in the next 90 days, and who does it. Notice that none of those five questions required you to decide what the discipline is called. That is the point.

The weak framing against the strong one

The weaker version treats the acronym as the strategy: buy AEO services, buy an AEO tool, report an AEO score. It produces a programme organised around vocabulary, which is why two vendors using different words can sell the same thing twice.

The stronger version organises around the four-step sequence and ignores the label entirely. Check access, make passages liftable, add sourced evidence, build off-site presence. It produces one programme, one budget line, and proposals you can actually compare.

Red flags you will genuinely hear

“AEO and GEO are completely different disciplines”, with no definition cited. “You need separate budgets for each.” “Our AEO score is proprietary”, meaning it cannot be audited. “GEO is about ChatGPT and AEO is about voice search”, a distinction with no current basis. “We guarantee citations.” “AI search is nothing like SEO”, contradicted by Google’s published position. And the quiet one: a proposal with an AEO line and a GEO line describing the same deliverables.

Five questions to ask

1. Which definition of AEO are you using, and where is it from? A good answer admits there is no canonical source.
2. What exactly differs between your AEO and GEO deliverables? A good answer is a list. A weak one is a philosophy.
3. Is this one programme or two, and one budget or two? A good answer is one of each.
4. Do you report per engine or averaged? A good answer is per engine, and can say why averaging is wrong.
5. Which of your published statistics can you link to a study? A good answer sends the links during the call.

It all comes down to one principle: judge the work, not the vocabulary. In a field where the academic survey itself says terminology remains heterogeneous, anyone selling you certainty about the words is selling you something else.

One closing note that costs us something. We use GEO as our umbrella term, and that is a convention rather than a claim to precision. Very few providers are equally strong across all four of measurement, execution, earned authority and attribution. Ours included. The good ones will tell you which is weakest, whatever they call it.

Where Pepper sits on this

Pepper is an agentic organic growth engine, and we run one programme rather than two.

• What you log into: workspace setup, brand profile, competitors and personas. GA4 and Search Console connected. Themes and prompts managed, GEO analytics read directly, and your own agents built and run in the Agent Atlas
• Engines tracked: 6, including ChatGPT, Perplexity, Gemini and Google AI Overviews, reported separately rather than averaged
• And a growth team is attached to the account, doing the work alongside your people across all four steps rather than splitting them by acronym
• Metrics reported: Brand Visibility, Domain Prompt Presence and Share of Voice, with the gap between the first two as the citability diagnostic
• Vocabulary: we use GEO as the umbrella term for consistency, not because the paper’s definition covers everything we do
• Where it falls short: we do not publish pricing, so you cannot size it before a call. A one-off audit is not what we are for, and our depth sits in content, authority and AI search rather than large technical migrations

Frequently asked questions

The basics

Are AEO and GEO the same thing?
Operationally yes. GEO has a formal definition from a 2023 paper published at KDD 2024. AEO has no canonical source. A July 2026 academic survey states terminology across the field remains heterogeneous, so no authority supports treating them as separate disciplines.

Where does the term GEO come from?
From “GEO: Generative Engine Optimization” by Aggarwal and colleagues, submitted November 2023 and published at KDD 2024. It introduced a black-box optimization framework and the public GEO-bench benchmark of user queries.

Where does the term AEO come from?
The search industry, at first around featured snippets and voice assistants, later broadened to cover AI answers. There is no founding paper and no canonical definition, which is why practitioners define it differently.

Does Google distinguish between AEO and GEO?
No. Google’s May 2026 guidance states that AEO and GEO are part of SEO, and that AI Overviews and AI Mode run on core Search ranking systems with no separate AI index.

Choosing and buying

Should I buy AEO services and GEO services separately?
No. If a proposal contains both as separate lines, ask which specific deliverables differ. In our experience they describe the same activities, and paying twice for one scope is the most common way this difference costs money.

Is LLMO another name for the same thing?
Effectively yes. LLM SEO, LLMO and AI search optimisation are all descriptive phrases rather than defined terms, and none traces to a canonical source the way GEO does.

Does the difference matter for tools?
Not much. Measurement platforms marketed as AEO tools and GEO tools cover largely the same vendor set and do broadly the same job, which is itself evidence that the difference is vocabulary.

What should I call it internally?
Pick one term and use it reliably, so proposals and reporting stay comparable. Which one you pick matters far less than not switching between them mid-programme.

Where to go next

Stop resolving the definition and start checking the four steps. Access, liftability, evidence, off-site authority. Every one of them is measurable and none requires you to settle the vocabulary.

Start with access, which takes ten minutes: open your robots.txt and check whether the AI search crawlers are allowed. Our engine-by-engine guide covers the tokens, each verified at the vendor’s own documentation.

For the fuller picture, GEO vs SEO vs AEO covers the three-way comparison and what genuinely changed, 18 GEO best practices covers what the research says gets cited, and how to run a GEO audit covers the five-stage diagnostic.

If you are choosing a provider, do you need an AEO agency or an AEO tool covers that decision directly. Our SalesHood case study documents AI Overview keywords moving from 14 to 97 across five months.

The honest exit. If you are reading this to settle an internal argument about terminology, settle it by picking one word and moving on. The hour spent on the difference is better spent checking whether your robots.txt lets the engines in.

Sources

Both terms were traced to their earliest locatable source. Where no canonical source exists, we have said so rather than supplying one.

• Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan and Deshpande, GEO: Generative Engine Optimization, arXiv, submitted 16 November 2023, published at KDD 2024. Introduces the term, a black-box optimization framework, and the GEO-bench benchmark. Reported visibility improvements up to 40% on 2023-era engines, which we cite as the origin of the term rather than as current performance data.
• Olivier Martinez, Optimizing Visibility in Generative Engines: A Critical Survey of Generative Engine Optimization (2023-2026), arXiv, 15 July 2026. Defines GEO as work that “seeks to increase content’s presence, likelihood of citation, or influence in answers produced by generative engines,” and states that “terminology, metrics, and evidence standards remain heterogeneous.”

Supporting research

• Google Search Central, AI features and your website, 15 May 2026. States that AEO and GEO are part of SEO, that AI Overviews and AI Mode use core Search ranking systems with no separate index, and advises against providers guaranteeing rankings.
• Zhang Kai, He Xinyue and Yao Jingang, From Citation Selection to Citation Absorption, arXiv, 28 April 2026. 602 prompts, 21,143 citations, 18,151 fetched pages. Academic and independent.
• Suzgun et al., Evaluating Commercial AI Chatbots as News Intermediaries, arXiv, 21 May 2026. 2,100 questions across six chatbots, on retrieval failure as a cause of answer errors.
• Muck Rack, Earned media still drives 84% of AI citations, 7 May 2026. More than 25 million cited links, 17 industries. Muck Rack sells PR software, so read it as an interested party with a large dataset.

On the absence of an AEO source: we searched for a founding paper or canonical definition and could not locate one. That is a statement about what we found, not proof that none exists. If a reader can point us at one, we will update this page and say so.