GEO vs SEO: what changes, and what stays the same

GEO vs SEO is mostly a false choice. Generative engine optimisation is a layer on top of SEO, not a replacement for it. Google's own guidance says SEO best practices still apply to AI Overviews and AI Mode. What GEO genuinely adds is access: making sure AI crawlers outside Google, such as OpenAI's and Anthropic's search crawlers, can actually reach your pages.

GEO vs SEO: what is the actual difference?

SEO is the work of helping search engines understand your pages and helping people choose to visit them. GEO, generative engine optimisation, is the same work aimed at systems that write an answer instead of listing ten links, and then cite a handful of sources inside it.

Google's SEO Starter Guide defines SEO as "helping search engines understand your content, and helping users find your site and make a decision about whether they should visit your site through a search engine." Nothing in that definition depends on whether the result is a blue link or a sentence in an AI answer. The difference between the two disciplines is narrower than the marketing around GEO suggests.

In our audits we split the work into two piles. The first pile is everything that makes a page crawlable, indexable, clear and trustworthy. That is SEO, and it carries straight over. The second pile is small: the checks that only matter because answer engines run on crawlers and retrieval systems that are not Googlebot. That second pile is where GEO earns its own name.

Is SEO still relevant for AI search?

Yes. Google answers this question directly in its guide to optimising for generative AI features: "In short, yes! The best practices for SEO continue to be relevant because our generative AI features on Google Search are rooted in our core Search ranking and quality systems."

The same guide goes further: "From Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO." It also describes grounding, where AI responses rely on core Search ranking systems "to retrieve relevant, up-to-date web pages from our Search index." In plain terms, if a page is not in the index, it is not in the pool the AI answer is built from.

That is why we treat "SEO in the age of AI" as SEO with a wider set of readers, not a new discipline. The fundamentals decide whether you are eligible at all. Everything else is refinement.

What stays the same in GEO vs SEO?

Almost everything that decides eligibility stays the same. Google's page on AI features and your website states that to appear as a supporting link in AI Overviews or AI Mode, "a page must be indexed and eligible to be shown in Google Search with a snippet," and that "There are no additional technical requirements."

Here is what we keep doing exactly as before:

• Getting pages crawled and indexed, and fixing anything that blocks either.
• Writing one clear H1 per page and descriptive headings that match the questions people ask.
• Answering the question early in the page, in plain words, so a passage can stand on its own.
• Linking related pages together so crawlers find them through links, not only through the sitemap.
• Publishing content that shows first-hand experience and that someone would trust.

Google's guidance on helpful, reliable, people-first content still applies word for word. It says SEO "can be a helpful activity when it is applied to people-first content, rather than search engine-first content," and that of the E-E-A-T aspects, "trust is most important." An answer engine choosing which passage to quote has the same problem a ranking system has: it needs a source it can rely on.

Some things people expect to change do not. Google's guide says you do not need new machine-readable files, AI text files or special markup to appear in its AI features, and that structured data "isn't required for generative AI search." It still recommends structured data as part of overall SEO, for rich result eligibility.

What does generative engine optimization add that SEO does not?

The genuinely new layer is access for crawlers that are not Google's. Google's guidance covers Google. It does not tell you whether the crawlers behind ChatGPT search or Claude can fetch your pages, and in our experience that is where sites quietly fail.

Classic SEO checks were built around Googlebot. If Googlebot gets a 200, the site looks healthy in Search Console. But a firewall, bot-management rule or CDN can treat other user agents differently, and none of that shows up in Google's tools. Google's AI features page lists "Ensuring that crawling is allowed in robots.txt, and by any CDN or hosting infrastructure" as a step, and that wording matters: robots.txt is only half of access.

So the GEO-specific checks we run are:

1. Read robots.txt and confirm each AI crawler you want is not disallowed, by name.
2. Request pages with each crawler's user agent and record the HTTP status, not just the robots.txt verdict.
3. Check firewall and bot-management rules for generic patterns that could match AI crawler names.
4. Re-test after any firewall or CDN change, because a fix in one layer can move a problem into another.
5. Decide deliberately which crawlers you allow, rather than inheriting whatever a security default chose.

On llms.txt, keep expectations straight. Google's guide says creating one "will neither harm nor help your site's visibility or rankings in Google Search, as Google Search ignores them." We still add one on client sites, because it is cheap and other systems may read it, but we do not sell it as a Google lever.

What we have seen: a firewall that only blocked the AI layer

One SEO Autopilot engagement shows the gap clearly. On a US healthcare analytics company's WordPress site, the firewall returned 403 to OpenAI's and Anthropic's search crawlers on every page. The trigger was a generic bad-bot rule matching the substring "searchbot". Eleven other crawlers passed.

The client's monitoring tool reported all sixteen AI crawlers as accessible, because it read robots rules instead of sending requests. By every classic SEO measure the site was reachable. For OpenAI's and Anthropic's search crawlers, it was not.

Between the baseline on 15 July 2026 and the re-measure on 18-19 August 2026, across all 39 sitemap URLs, AI crawler access went from 45 to 82 and AI Visibility from 18.35 to 66.35. It was not free: performance fell from 48 to 28, because removing the firewall rule took the CDN edge cache with it, and median time-to-first-byte rose from 0.42s to 2.39s. That trade-off is exactly the kind of thing GEO work has to manage alongside SEO, not instead of it. We wrote up the crawler side in more detail in how a firewall blocked AI crawlers.

GEO vs SEO side by side

The table sets out where each discipline sits. Most rows are shared.

How should you split effort between GEO and SEO?

Fix the shared foundations first, then add the GEO layer on top. A site with indexing problems, missing H1s or thin pages will not be rescued by AI-specific tweaks, and Google's guidance says plainly that its AI features run on the same systems.

A practical order we use:

1. Confirm the important pages are indexed and eligible for a snippet.
2. Fix templates that break headings, titles or internal links across many pages at once.
3. Rewrite key pages so each section opens with a direct answer.
4. Test AI crawler access with real requests, not only robots.txt rules.
5. Add or tidy structured data and an llms.txt file, without expecting either to move Google rankings.

If you want a first look at the access layer, our free AI visibility checker reads robots.txt rules for 11 AI crawlers and requests your homepage once with each crawler's user agent. That is the checker's own request, not the real crawler's, and it covers the homepage only, so treat it as a starting signal rather than proof. For the full picture across your site, the GEO and AEO audit covers both piles. If the naming itself is confusing, AEO vs GEO untangles the acronyms.

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