AEO vs SEO

AEO vs SEO:
what actually changes.

SEO gets your pages into Google. AEO gets your content cited by AI. They are not the same thing, and optimising for one does not automatically optimise for the other.

By Neil Walsh · June 2026 · 6 min read

TL;DR
  • SEO ranks pages in Google. AEO gets content cited in AI answers.
  • Good SEO is a foundation, not a guarantee of AEO visibility.
  • The biggest AEO-specific signals are schema markup, conversational structure, and AI crawler access.
  • You need both. They measure different things.

What is SEO?

Search Engine Optimization is the practice of making pages rank higher in search engines, primarily Google. The goal is to appear in the list of ten blue links when someone types a query. SEO signals include backlinks from other sites, keyword relevance, page speed (Core Web Vitals), and technical factors like crawlability and indexability.

SEO has been the dominant model of organic search visibility since the late 1990s. It is well understood, well tooled, and well measured. Google Search Console, Ahrefs, Semrush: the entire industry is built around it.

What is AEO?

Answer Engine Optimization is the practice of structuring content so that AI systems choose to cite your site when generating responses. The target is not a ranking position. It is a citation. When a user asks ChatGPT "what is the best project management tool for startups?" and the response references your product, that is AEO working.

AEO emerged as a distinct discipline in 2023-2024 as AI assistants became primary research tools for a significant portion of users. The same user who would have previously Googled a question now asks ChatGPT or Perplexity instead, and never sees a list of ranked pages at all.

AEO is also referred to as GEO (Generative Engine Optimization). The terms are used interchangeably, but the distinction is worth spelling out.

What about GEO?

There are three terms in circulation and they are easy to confuse. SEO is the oldest: optimising for Google and Bing rankings. AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) both describe optimising for AI systems, and in practice most practitioners use them as synonyms. Where a distinction is drawn, AEO is sometimes used more narrowly for voice assistants and featured snippets, while GEO covers large language model chat interfaces such as ChatGPT, Claude, and Gemini.

For this article the terms are treated as equivalent, because the underlying signals (schema markup, crawler access, conversational structure, named authorship) are the same regardless of which term a given AI vendor or blog post prefers. See what is AEO and what is GEO for the full breakdown of each term.

Where they overlap

The foundations of good SEO are also the foundations of good AEO. A fast, secure, well-structured site with clear meta tags and no crawl errors performs better on both. E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) matters to both Google and AI citation engines.

So if you have done solid SEO work, you are not starting from zero. You have a head start on roughly 40% of what AEO requires.

Where they diverge

The 60% that differs is significant. AI citation engines weight signals that traditional SEO largely ignores:

  • Structured data (Schema.org): especially FAQPage, Article, Organization, and HowTo schemas
  • AI crawler access: if GPTBot or ClaudeBot is blocked in robots.txt, you cannot be cited regardless of content quality
  • Conversational phrasing: content written as direct answers to questions is cited more than keyword-optimised prose
  • llms.txt: an emerging standard that tells AI systems what your site is and what to index
  • Named authorship: a Person schema with a real name is a stronger E-E-A-T signal for AI than an anonymous Organisation

Backlinks, the single most important SEO signal, have little direct weight in AI citation. A site with zero backlinks but excellent structured data and clear conversational content will outperform a high-DA site with no schema in AI responses. This is the biggest practical difference between the two disciplines.

A real-world example

Take two SaaS pricing pages with identical Google rankings, both sitting at position 8 for their category term. Page A has a clean, keyword-optimised layout: a pricing table, a bulleted feature list, and a strong backlink profile from review sites. Page B has the same pricing table, but also FAQPage schema answering "how much does it cost", "is there a free trial", and "what happens if I cancel", plus a named author bio and a clear one-sentence summary of what the product does at the top of the page.

Ask ChatGPT or Perplexity "what does [product] cost and is there a free trial", and Page B is the one that gets cited. Its Google position does not change: the SEO signals (backlinks, keyword relevance) are unchanged. But its AI visibility is materially better, because the FAQ schema and the direct-answer phrasing give the AI model a ready-made, attributable answer to lift. Page A, despite ranking identically in Google, is invisible in the AI answer.

This is the pattern seen across most AEO audits: the pages that get cited are rarely the highest-authority pages. They are the pages that answer a specific question in a format an AI model can lift cleanly and attribute confidently.

Which should you prioritise first?

Three questions decide where to start:

  • Are you already ranking on page one of Google for your key terms? If not, fix SEO fundamentals first: AEO cannot compensate for a page Google has not indexed or cannot find.
  • Does your audience research products by asking an AI assistant rather than searching? B2B, SaaS, and technical audiences increasingly do. If yes, AEO signals (schema, direct answers, named authorship) pay off faster than incremental SEO gains.
  • Is your content already well-structured but under-cited by AI? If your Google rankings are solid but you see no AI referral traffic, the gap is AEO-specific and the fix is schema and conversational structure, not more backlinks.

In practice, most sites should not choose one or the other. Run an AEO audit alongside existing SEO tracking, then prioritise whichever gap is largest: unindexed pages point to SEO work, cited-nowhere pages with good rankings point to AEO work.

The practical implication

If your marketing strategy is built entirely on Google rankings, you are optimising for a channel that is shrinking in relative importance. AI search is not replacing Google overnight, but it is capturing a growing share of research and discovery queries, particularly in B2B and SaaS markets.

The most effective strategy is to do both: maintain your SEO fundamentals, and layer AEO-specific signals on top. The good news is that most AEO improvements are one-time implementation tasks (adding schema markup, rewriting a few pages in conversational format, updating robots.txt) rather than ongoing campaigns like link building.

Side-by-side comparison

SignalSEOAEO
Primary targetGoogle / Bing indexChatGPT, Claude, Gemini, Perplexity
GoalRank in blue link resultsGet cited in AI-generated answers
Key ranking factorBacklinks + keyword relevanceStructured data + content clarity
Schema markupHelpful but not requiredCritical: FAQPage, Article, Org
Content formatKeyword-dense, long-formConversational, definition-first
Author signalsMinor factorStrong E-E-A-T signal for citation
robots.txtBlock bad botsMust allow GPTBot, ClaudeBot etc.
Page speedCore Web Vitals ranking factorIndirect: slow sites get crawled less
Meta descriptionClick-through rate leverSometimes used as citation snippet
llms.txtNot applicableEmerging standard for AI crawlers
Measurement toolGoogle Search Console, AhrefsCiteRank AEO audit

How AI engines read the web

Answer engines reach the open web through dedicated crawlers. According to each provider's documentation, OpenAI's GPTBot, Anthropic's ClaudeBot, Google-Extended, and PerplexityBot all respect robots.txt directives.

These engines lean heavily on Schema.org structured data, the vocabulary backed by Google, Microsoft, Yahoo, and Yandex. GPTBot and Google-Extended both launched in 2023, and the share of research queries that begin inside an AI assistant has climbed every quarter since.

According to Google's own documentation, structured data helps machines understand what a page is about. Research on AI answer quality shows that pages with a clear heading hierarchy, direct definitions, named authorship, and outbound citations to authoritative sources are quoted far more often than thin or anonymous pages. The data shows the same pattern across all four major engines: clarity and provenance beat keyword density.

Frequently asked questions

What is the difference between AEO and SEO?

SEO targets Google and Bing: the goal is to rank in a list of blue links. AEO targets AI systems like ChatGPT, Claude, Gemini, and Perplexity: the goal is to be cited directly in an AI-generated answer. The signals overlap but are not identical.

Do I need AEO if I already do SEO?

Yes. A site can rank on page one of Google and be completely absent from AI responses. As AI search adoption grows, AEO becomes a separate visibility channel that requires its own optimisation strategy.

Does good SEO help with AEO?

Partially. Technical fundamentals (fast pages, clean URLs, HTTPS, solid meta tags) help both. But the signals that drive AI citation most (FAQPage schema, clear definitions, author markup, conversational phrasing) are largely invisible to traditional SEO tools.

What is GEO and how does it relate to AEO?

GEO (Generative Engine Optimization) is another term for the same practice. In practice, the terms are used interchangeably in 2025-2026. Both refer to optimising content to appear in AI-generated responses.

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