GEO vs SEO: What Actually Changes When AI Answers Replace Search Results

Search Google for "best CRM for a ten-person agency" and you get a page of links, each one a position you can compete for. Ask ChatGPT the same question and you get a single answer that names three or four products and cites a handful of sources. Generative engine optimization — GEO — is the effort to be one of those names and one of those sources.

The short version: GEO is mostly SEO with a different scoreboard. The primary sources — Google's own guidance, OpenAI's crawler documentation and the research paper that coined the term — agree on more than the GEO hype suggests, and disagree with some of the advice being sold under the label. This piece separates the two, then covers crawler access, measurement, and where paid placements in AI answers fit.

What are GEO and AEO?

Generative engine optimization was named in a 2023 research paper, later accepted to KDD 2024, as a way for content creators to improve how visible their content is in answers produced by AI systems that search the web and summarise what they find. Answer engine optimization is an older label from the featured-snippet and voice-assistant era, and today it is used for much the same goal: being the source an AI answer draws on. In practice the two terms are interchangeable; our glossary entry covers both.

The goal differs from classic SEO in one way that matters. SEO measures where a page ranks. GEO measures whether a brand or page is mentioned, quoted or cited inside an answer — and how prominently.

GEO vs SEO: what stays the same?

More than most GEO advice admits. Google's guidance on AI features is blunt: "There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary." To be shown as a supporting link, a page has to be indexed and eligible for a snippet in ordinary Google Search. The same fundamentals apply:

• Crawling allowed in robots.txt, and by your CDN or hosting firewall
• Content findable through internal links
• Important content available as text, not only in images or scripts
• Structured data that matches what the page visibly says
• Helpful, reliable content written for people

Google also says you do not need "new machine readable files, AI text files, or markup" to appear in these features, and that there is no special schema.org structured data to add. That includes llms.txt: whatever its value elsewhere, Google does not require it for AI Overviews or AI Mode.

What actually changes?

Two of these deserve a closer look. First, answers are assembled, not ranked. Google says AI Overviews and AI Mode may use a "query fan-out" technique, issuing several related searches across subtopics to build one response. The practical inference is that a page answering a specific sub-question well can be pulled into an answer for a broader query it would never rank for on its own.

Second, a win may not produce a visit. A brand named in an answer can influence a decision without a click. That makes GEO harder to measure than SEO, which is the subject of a section below.

What does the GEO research actually say?

The GEO paper tested nine ways of rewriting web content and measured how visible each rewritten source became in AI-generated answers. Three methods performed best: citing sources, adding quotations from credible sources, and adding statistics. They improved visibility by 30–40% on the paper's main word-count metric and 15–30% on its subjective measure. Keyword stuffing — the classic SEO shortcut — "often perform[s] worse."

Two other findings are useful. Lower-ranked websites gained more from these methods than top-ranked ones, which suggests GEO can reward smaller sites with better-supported content. And the authors found that what works varies by domain.

The limits matter as much as the headline. The experiments ran on the authors' own benchmark of queries and on Perplexity, where they reported gains of up to 37%. They were not run on Google's AI features or on ChatGPT search, and AI search products have changed a great deal since the paper was written. Read "up to 40%" as evidence of direction, not as a forecast for your site.

The durable lesson is reassuring: the methods that worked — sourcing claims, quoting people who know, using specific numbers you can stand behind — are also what make a page more useful to a human reader.

Can AI crawlers reach your site?

Access is the one place where GEO needs a genuinely new check, because each AI company runs its own crawlers with separate controls. OpenAI's crawler documentation lists them:

• OAI-SearchBot surfaces sites in ChatGPT's search features. Sites that block it "will not be shown in ChatGPT search answers," though they can still appear as navigational links.
• GPTBot collects content that may be used to train OpenAI's models. Blocking it is a training opt-out; it does not remove you from ChatGPT search.
• ChatGPT-User fetches pages when a user asks ChatGPT to. OpenAI says it is not used to decide whether content appears in search.
• OAI-AdsBot only visits landing pages submitted as ads.

OpenAI notes that robots.txt changes take about 24 hours to affect search results. On Google, Googlebot is the control for AI Overviews and AI Mode, with snippet controls such as nosnippet and max-snippet limiting what is shown; a separate token, Google-Extended, covers training and grounding in some of Google's other AI systems. Check your CDN and firewall as well as robots.txt: bot protection that blocks unfamiliar user agents can quietly block the crawlers you want.

How do you measure AI visibility?

Imperfectly, with several partial signals rather than one report:

• Search Console includes clicks and impressions from AI Overviews and AI Mode in its overall Web search data. You will not get a separate AI line, but the traffic is counted.
• Referral traffic from AI assistants shows up in your analytics as visits from their domains. Track those as their own channel.
• Crawler activity tells you which AI systems are reading your pages. Most AI crawlers never run JavaScript, so browser analytics does not see them. On our own site we measure them from server logs instead, which is how we know which AI systems are actually reading our pages.
• Answer sampling means asking a fixed set of buyer questions in the assistants that matter to you, on a regular schedule, and recording whether and how you are mentioned. Answers vary between runs, so treat this as a trend, not a score.

Where do paid placements fit?

GEO has a ceiling that no amount of optimization removes: the model decides. OpenAI states that ads do not influence ChatGPT's answers and that advertisers cannot shape or rank its responses. Ads appear separately, below the answer, and are labelled as sponsored.

Organic visibility in AI answers is earned and never guaranteed: no one can pay to be cited. Paid placements are the part of AI visibility a brand controls, and we think most brands will need both. GEO builds the credibility that gets you cited; paid placements make sure you are present in the conversations that matter while that credibility builds.

If you want to test the paid side, our guide to advertising on ChatGPT covers how buying works today, and Thrad's self-serve platform lets you launch campaigns across AI conversations. For the wider category, see our overview of conversational advertising.

A GEO checklist

1. Confirm OAI-SearchBot, Googlebot and the other crawlers you want are allowed in robots.txt and not blocked by your CDN or firewall.
2. Make sure every page you want cited is indexed, internally linked and readable as text.
3. Back claims with sources, quotations from credible people and specific figures you can defend.
4. Answer the sub-questions around your topic, not only the head term.
5. Keep structured data consistent with what the page visibly says.
6. Set up AI referral tracking, server-side crawler logging and a monthly answer-sampling routine.
7. Decide which buyer conversations you need to be present in regardless of citation, and plan paid placements for those.