SEO vs AEO vs GEO: What's the Difference and Does Your Business Need All Three?

In the last two or three years, two new acronyms have appeared alongside SEO: AEO (answer-engine optimisation) and GEO (generative-engine optimisation). Agencies now sell all three as distinct services, and a Managing Director reading about them could reasonably conclude there are three separate technical disciplines a business now needs to invest in.

The frank answer is more useful than that framing suggests: AEO and GEO are largely industry labels for applying long-standing SEO and content principles to AI-generated answers, not a proven separate technical mechanism. There is a genuine shift in buyer behaviour behind the labels — more people now ask AI assistants direct questions — but the practical response overlaps heavily with doing SEO and content well. This article sets out what each term means, where they genuinely differ, and what is worth your attention.

What each term actually means

SEO (search engine optimisation)

The established discipline of making a website easier for search engines like Google and Bing to crawl, index and rank well for relevant queries. Documented by Google itself (Search Essentials, SEO Starter Guide) with clear, if incomplete, public guidance.

AEO (answer-engine optimisation)

An industry term, not a term used by Google, OpenAI or any major platform, for optimising content so it is more likely to be selected as a direct answer — in a Google featured snippet, an AI Overview, or an AI assistant's response — rather than simply ranking as a listed page.

GEO (generative-engine optimisation)

A newer, broader industry term for optimising content specifically for generative AI systems (ChatGPT, Gemini, Perplexity and similar), covering how content is structured, phrased and corroborated so an AI model is more likely to draw on it when generating an answer.

FACT: none of "AEO" or "GEO" appear as defined terms in Google's, OpenAI's, Microsoft's or Perplexity's official documentation. They originate from the SEO and marketing industry describing an observed shift in how content gets used, not from the platforms themselves. That does not make the underlying advice wrong — much of it is sound — but it means the labels should be read as marketing shorthand, not as evidence of a separately engineered ranking system a business can optimise against with precision.

The overlap and the difference, side by side

The pattern in that table is deliberate. FACT: Google states directly that there are no special requirements or extra optimisation needed to appear in AI Overviews or AI Mode beyond normal Search eligibility — a page simply needs to be indexed and eligible to rank; standard SEO best practice applies (Google Search Central, "AI features and your website"). That single documented statement undercuts a large part of the commercial case for treating AEO as a separate discipline from SEO, at least where Google's own AI features are concerned.

Where GEO genuinely adds something

GEO is the newer and less overlapping of the two labels, because it concerns platforms Google's documentation does not cover: ChatGPT, Gemini, Perplexity and Copilot as standalone products, which have their own crawlers, their own training processes and their own undocumented retrieval logic. Three things genuinely sit outside classic SEO here, and are worth treating as distinct considerations:

• Crawler access decisions: whether to allow GPTBot, OAI-SearchBot, ChatGPT-User, PerplexityBot and similar — a robots.txt decision with no equivalent in classic SEO, covered in a dedicated article in this series.
• Training-data presence vs live retrieval: whether a model may already "know" about a company from training, separately from whether it can retrieve the current website live, a distinction that does not exist in traditional search.
• No analogous reporting tool: Google Search Console tells you about indexing and ranking; no AI provider offers an equivalent tool showing when or how often your business was mentioned in an AI answer.

Beyond those three points, most GEO advice in circulation — write clearly, answer the actual question, be specific, get corroborated by third parties, keep the site technically crawlable — is simply good SEO and good content practice restated for a new audience.

Myths vs reality

• Myth: GEO is a proven, separate ranking algorithm you can optimise for precisely. Reality: no AI provider publishes a retrieval or citation algorithm; GEO techniques are best-practice inference, not confirmed mechanics.
• Myth: AEO/GEO content needs a totally different structure from SEO content. Reality: direct, specific, well-organised content with a clear answer near the top helps featured snippets, AI Overviews and AI assistants alike — it is the same underlying discipline of clarity.
• Myth: schema markup or an llms.txt file guarantees AI citation. Reality: schema helps machines parse facts but does not guarantee citation or ranking; llms.txt is a community proposal with no public commitment from any major AI provider to use it, and Google has said it does not use it.
• Myth: doing AEO/GEO means you can deprioritise SEO. Reality: Google Search still drives the large majority of documented, measurable B2B web traffic for most companies; AI answers are an addition to be visible in, not yet a replacement channel with equivalent reach or reporting.

Is SEO dying?

No, on current evidence. OBSERVATION: AI assistants are a genuinely growing behaviour, and some buyers now skip a traditional search results page entirely for certain questions. But Google Search remains, by a wide margin, the most measurable and highest-volume route most B2B companies have to buyer attention, and AI systems themselves often draw on the same indexed web content that SEO exists to make accessible and clear. Treat AI visibility as an additional surface to be found on, built from the same foundation, not as a signal to abandon search fundamentals.

Does the same content work in Google and in AI answers?

Largely yes. A specific, clearly written page that directly answers a real buyer question, backed by accurate structured data and corroborated by third-party sources, is well positioned for a Google ranking, a Google AI Overview, and an AI assistant's answer simultaneously — because all three are, at root, looking for clear, trustworthy, specific material. The exceptions are the crawler-access and platform-presence questions above, which require their own deliberate decisions rather than content changes.

A practical way to think about budget and effort

1. 01Get the SEO and content foundations right first — crawlable site, clear pages per service and location, specific content answering real buyer questions. This is the majority of the value, and it serves Google, AI Overviews and AI assistants at once.
2. 02Make a deliberate, documented decision on AI crawler access (allow or block GPTBot, OAI-SearchBot, PerplexityBot and similar) rather than leaving it to default settings.
3. 03Add accurate structured data confirming organisation, service and location facts, understanding it helps clarity rather than guaranteeing citation.
4. 04Treat ongoing third-party corroboration (reviews, press, directories, industry mentions) as part of the same programme, not a separate GEO task.
5. 05Measure what is measurable (indexing, ranking, traffic) and treat AI mentions as a directional signal checked manually, not a reported metric.

What a business genuinely needs

Most B2B companies do not need three parallel strategies called SEO, AEO and GEO. They need one coherent programme — a technically sound, clearly structured website with specific, well-corroborated content — applied with awareness of the handful of genuinely new decisions AI platforms introduce (crawler access, structured data accuracy, and accepting that AI mention measurement is immature). Evans's Search & AI Visibility service is built on that basis: ongoing monitoring and improvement of which buyer questions a business is found for and where it is cited, across Google and AI systems together, without selling AEO or GEO as a separate product that does not reflect how these systems actually appear to work.