GEO vs SEO: what changes and what does not

Generative engine optimization was named in a research paper first published in 2023 and presented at the KDD conference in 2024. It set the new work against search engine optimization: in SEO, a site’s visibility is its average ranking over a range of queries, while a generative engine combines several sources in one answer, so a ranking no longer describes how visible a source is^[1].

Three names now circulate for overlapping work. SEO is the whole of it. AEO is the part that makes a page the clean answer to one question, and grew up with featured snippets. GEO is the part that earns a place among the several sources an AI answer is written from. A dimension-by-dimension table of what GEO keeps from SEO and what it changes opens the practical guide to generative engine optimization; this guide is about what the difference means for the work on your own site.

For Google, the two are one system. Its generative AI features are rooted in its core Search ranking and quality systems: they retrieve pages from the Search index, a technique Google also calls grounding, and show links to the pages that support the answer^[2]. There are no additional requirements to appear in AI Overviews or AI Mode beyond those of Search^[3].

Microsoft says the same of its assistants: crawlability, metadata, internal linking and backlinks remain essential for content to be discoverable, and are the starting point^[4]. So the groundwork is shared:

• Pages that crawlers may fetch and that search engines index.
• Content that answers the question better than the pages around it. Google asks for non-commodity content with a point of view of its own, not a restatement of what is already available elsewhere^[2].
• A clear structure: headings, internal links, and the important text in the HTML rather than in images.
• A reputation that other sites state in their own words.

Three differences are large enough to change how the work is organised.

The answer is assembled, not ranked, so what a page says weighs more than where it ranks. In the paper’s tests, when a page ranked fifth added citations, its visibility rose 115.1%; a top-ranked page that did the same lost 30.3% on average^[1]. What else the research found, and its limits, is in the research section of the practical guide.

More crawlers need access. Several AI services run a search crawler of their own, separate from their training crawler. OpenAI’s OAI-SearchBot decides whether a site can appear in ChatGPT search answers, while GPTBot concerns training^[5]. Sites treat the two jobs differently: in the October 2026 edition of QueryRev Research’s State of AI crawler access study, the training crawlers it measures are blocked by name on 7.9% of the top sites read on average, the AI search crawlers on 4.8%^[6]. Each is allowed or refused by its own group in robots.txt, and which ones to allow is a decision of its own.

Success is often out of sight of analytics. A mention in an answer can shape a decision without a click. Rankings and clicks still count for SEO; GEO adds mentions and citations, counted over a fixed set of prompts, which no analytics tool records by itself. The metrics and KPIs that matter defines them.

Much of what is sold as GEO on top of this is a shortcut: special files for AI, placed mentions, a page for every variant of a question. Google lists what you can ignore, and the practical guide’s last section sets it out.

The weight of GEO against classic SEO is not the same for every query. Google’s own descriptions of its AI features show where an answer is likely to stand between the searcher and your page, and where it is not.

Read your own query list against this table before you split the budget. A site whose demand is mostly simple, navigational queries has less to gain from GEO than one whose buyers ask long, comparative questions, and the second is the one to watch first.

Because the foundation is shared, most GEO work is SEO work done with the answer in mind. A useful way to plan it is to sort each task by the result it serves.

Answer-first writing is the task with the most overlap, and the one most worth doing well; answer engine optimization has its own guide.

Four checks, in this order, show how much of your search work needs the GEO angle and where it should go first.

1. 1Look at your query list for AI Overviews. Log which of your important queries show one, and whether it cites you, as set out in how to track AI Overviews.
2. 2Check that the AI search crawlers may fetch your pages, in robots.txt and in the firewall or CDN in front of the site. A blocked crawler makes every later step useless.
3. 3Ask the main assistants a few of the questions buyers ask about your category and your brand, and read what they say. How to track your brand in ChatGPT turns this into a repeatable check.
4. 4Run the GEO audit checklist on the pages behind the questions where you are absent or described wrongly, and put its findings in the same queue as the rest of your SEO work.

Report the two in one place, against the same pages. Search Console already counts traffic from Google’s AI features within the Web search type of its Performance report^[3], so classic and AI clicks on Google arrive together. The AI side adds a prompt set tracked across assistants, and the platform reports that count citations.

1. 1Choose the pages that matter to the business, and keep one list for both.
2. 2For each page, report clicks and impressions from search, and the prompts in which it is cited or the brand is named.
3. 3Read a fall in clicks next to the AI data before calling it a ranking loss: an answer that cites the page can take the click the page used to get.
4. 4Count enquiries and sales by page, so both kinds of visibility are judged by what they bring in.

How to run that measurement and report it, from the baseline to the monthly page, is set out in how to measure GEO results.