Answer engine optimisation, or AEO, is the practice of writing and structuring content so that a system which answers a question directly uses your page as the source of that answer. The systems in question are Google’s AI Overviews and AI Mode, ChatGPT, Perplexity, Copilot, Gemini and voice assistants. Success is measured in citations and named mentions inside answers rather than in clicks.
Which is the same sentence you would write for generative engine optimisation, with two words swapped. That is the honest starting position. The rest of this page is about what happens when you test it.
Answer visibility holds the rest of that testing: the four labels, the overlap with ordinary search results and the five ways any of it gets measured.
Is AEO actually different from GEO?
Not in any settled sense. Wikipedia’s entry on the subject puts it plainly:
No consensus definition distinguishing these terms had been established in the academic literature as of early 2026, and the terms are frequently used interchangeably in trade and practitioner contexts.
GEO at least has an origin. It was named in a 2023 arXiv paper, later published at KDD 2024, which proposed the term and a benchmark to go with it. AEO has no equivalent. No paper, no owner, no defining document. It arrived through practitioner writing, mostly out of the older work on featured snippets and voice search. It now covers whatever the person using it sells.
So anyone drawing a firm boundary between the two is describing a service, not a distinction. Worth knowing which you are being sold.
What do the search results say?
Practitioners use the two words interchangeably. The search results do not, which is checkable, so we checked.
Method. Ahrefs serp-overview, GB market, 10 August 2026, top ten positions for “answer engine optimisation” and for “generative engine optimisation”. Both queries in UK spelling. We compared the organic results by domain.
“Answer engine optimisation”, GB, organic results
| # | Domain | Page | DR | Ref. domains |
|---|---|---|---|---|
| 2 | pwc.com | What is Answer Engine Optimisation? | 91 | 11 |
| 3 | hubspot.com | AEO guide | 93 | 261 |
| 5 | reddit.com | r/localseo thread, “What is AEO?” | 95 | 32 |
| 6 | coursera.org | What Is Answer Engine Optimization? | 91 | 115 |
| 7 | youtube.com | Introduction to AEO | 99 | n/a |
| 8 | siteimprove.com | What is Answer Engine Optimization | 81 | 18 |
| 9 | forbes.com | AEO, what brands need to know | 94 | 136 |
| 10 | cxl.com | AEO, the complete guide | 85 | 408 |
“Generative engine optimisation”, GB, organic results
| # | Domain | Page |
|---|---|---|
| 2 | developers.google.com | Google’s guide to optimizing for generative AI features |
| 3 | en.wikipedia.org | Generative engine optimization |
| 4 | coursera.org | What Is Generative Engine Optimization? |
| 6 | semrush.com | GEO, a practical guide |
| 7 | aspectusgroup.com | A beginner’s guide to GEO |
| 8 | mailchimp.com | GEO, the future of SEO |
| 9 | contentful.com | What is GEO and how does it work |
| 10 | found.co.uk | GEO best practices |
No link figures on the second table, deliberately. Ahrefs returned root or truncated URLs for several of those results, so the referring-domain counts it reports against them are domain-level rather than page-level and would not be comparable with the first table. The second table is here for the domain names only.
Eight organic results each. One domain appears on both: Coursera. Google has built two source sets that agree on a course provider and nothing else.
Three readings follow from that.
The interchangeable terms do not have interchangeable competitors. If you are writing one page to cover both labels, you are writing against sixteen pages rather than eight. The two sets have almost nothing in common. That is either the reason to write it or the reason not to, but it is not a free ride.
Nobody selling the service is in the AEO result. The GB result for “generative engine optimisation agency” is ten UK agencies competing for the query. The result for “answer engine optimisation” is PwC, HubSpot, Reddit, Coursera, YouTube, Siteimprove, Forbes and CXL. Not one agency. The demand data says why: “answer engine optimisation agency” carries 100 searches a month in the UK against 700 for “generative engine optimisation agency” (Ahrefs, GB, 10 August 2026). Buyers ask for GEO. Readers ask about AEO.
The cheap position is at the top. PwC holds position two on eleven referring domains. HubSpot sits below it on 261 and CXL on 408. Whatever is deciding this result, it is not links.
What does the AI Overview cite for each?
Both queries return an AI Overview at position one. Not every term in this vocabulary does: “aeo vs geo”, “aeo agency” and “answer engine optimisation agency” returned no SERP features at all on the same date, which is its own small signal about how young the commercial end of this category still is.
The AEO overview cited five sources on 10 August 2026: a Reddit thread in r/localseo, HubSpot’s AEO guide, Coursera, Siteimprove and a Canadian web design studio’s blog post. The GEO overview cited eight, of which we could attribute Wikipedia, Semrush and Coursera by title. The rest were returned as Google redirect URLs that do not resolve to a domain, so they are not claimed here.
Coursera again. The only source both answers agree on.
A word on how much weight that carries. This is one pull, on one day. A previous check of ours on a different term returned a different citation set a few hours later on the same date, so a single reading of any AI Overview is a snapshot rather than a measurement. We tried to pull a June snapshot of the same result to measure the drift and Ahrefs returned no rows for that date, so the change over time is unmeasured rather than stable. The domain overlap above is drawn from the organic results, which are considerably steadier than the overview.
What about the spelling?
Same split that runs through this whole category. It is worth real money.
| Keyword | GB volume | Difficulty |
|---|---|---|
| aeo | 1,000 | 22 |
| answer engine optimisation | 600 | 49 |
| answer engine optimization | 600 | 0 |
| aeo agency | 250 | n/a |
| aeo vs geo | 200 | n/a |
| answer engine optimisation agency | 100 | n/a |
Identical volume on the two spellings, forty-nine points of difficulty apart. Difficulty is computed from the pages that currently rank. The two spellings return different pages, so the gap is not about language. It records how few people have written the British version.
Note the direction, because it is the opposite of the GEO term. On generative engine optimisation the British spelling is the cheap door at difficulty 0. On answer engine optimisation the American spelling is. Anyone repeating “always use UK spelling” as a rule has not looked at the numbers for the specific term.
So which one should you buy?
The label changes nothing about the work. What changes is the scope of what gets measured. Pin that down before you sign anything.
Ask which surfaces are in the report. An AEO brief written by someone who came up through featured snippets often means Google only. A GEO brief usually means the chat assistants. Your buyers use both, so a contract covering one is half a job at a whole price.
Ask what counts as a result. A featured snippet is a rank. A citation in ChatGPT is not. If the reporting pack has positions in it, the work being sold is closer to SEO than to either label, which is defensible on Google’s own guidance and dishonest to charge a premium for.
Ask who chose the prompt set. If the agency picks it, the agency picks the score.
The uncomfortable part
Google’s position is that all of this is still SEO. On its own surfaces it has a case. The eligibility requirements for AI Overviews are indexing, snippet eligibility and ordinary technical health. Nothing exotic.
Where that argument stops is off Google. ChatGPT and Perplexity retrieve from their own indexes, cite different sources, answer questions nobody types into a search box. A brand can be fine in Google and absent everywhere else, which no ranking report will ever show you.
That is the whole reason for the vocabulary. It is not a good reason for four competing labels.
Next: what generative engine optimisation actually is covers the paper, Google’s guidance and what decides whether a model quotes a page. LLM SEO, explained without the jargon does the same for the third label in this vocabulary. What AI visibility means and how to measure it covers the five measurement methods and where each one misleads. If you would rather check your own position before reading anything else, the afternoon method is here.
Data in this article: Ahrefs serp-overview and keywords-explorer-overview, GB, 10 August 2026. Wikipedia’s generative engine optimization entry, read 10 August 2026.