Short answer
SEO gets a page ranked in search results. AEO (answer engine optimization) and GEO (generative engine optimization) get a brand named and cited inside the answers AI assistants write: two names for one goal, seen from different sides, and LLMO (LLM optimization) is a third. What stays is the foundation, a site that can be crawled, indexed and trusted. What changes is the unit of success, the signals that win citations and how results are measured.
Key takeaways
- SEO competes for a position in a list of results. AEO and GEO compete to be quoted inside one composed answer.
- AEO, GEO and LLMO describe overlapping work. In my programs they run as one piece of work on one SEO foundation.
- What stays: crawling, indexing, content quality and authority. Google says the best practices for SEO remain relevant for its AI features.
- What changes: the passage becomes the unit of success, each engine picks its sources its own way, and visibility is measured in citations and share of voice.
- Rankings show part of the picture. In one Ahrefs study, 12% of the links cited by ChatGPT, Gemini and Copilot ranked in Google’s top 10 for the same prompt.
What AEO, GEO, SEO and LLMO mean
SEO, search engine optimization, is the work of getting pages ranked and clicked in search results. Its unit is the page, and its scoreboard is the results page with the features around it.
AEO, answer engine optimization, is the work of getting a brand named and linked inside the answers AI assistants give, in ChatGPT, Perplexity, Gemini, Copilot, Google AI Overviews and AI Mode. I cover it in full in What is answer engine optimization (AEO)?
GEO, generative engine optimization, names the same goal from the retrieval side. The term comes from a 2023 research paper by Pranjal Aggarwal and colleagues, later accepted at KDD 2024, which reported that the methods it tested raised a source’s visibility in generative engine responses by up to 40% [1]. GEO work concentrates on how retrieval systems pick the passages they quote.
LLMO, LLM optimization, is the third name and the loosest. People use it for the same work, with the emphasis on the language models behind the assistants. The three names overlap more than they differ, so in my programs AEO, GEO and LLMO run as one piece of work on one SEO foundation.
What stays the same
An assistant can cite only what it can find, and it finds its sources through search indexes and its own crawlers. The foundation therefore stays where SEO built it: pages that can be crawled and indexed, content that answers the question well, a fast and stable site, and other trusted sites that point to yours.
Google is explicit about its own AI features. Its guidance says the best practices for SEO remain relevant for AI Overviews and AI Mode, and that appearing in them needs no additional requirements or special optimizations [2]. Clicks from those features are reported in Search Console’s Performance report, inside the Web search type [2], so the reporting you already have keeps counting them.
The research stays too, with a wider brief. The questions buyers ask are still the starting point. What grows is the number of related questions each answer draws on.
What changes for AI answers
Four things change, and each one changes the work.
The unit of success
SEO wins with a page. An assistant quotes a passage, so each important question needs a few sentences that answer it directly, near the top of a section, with the specifics a model can lift: numbers, named tools, dates.
The questions behind each answer
An assistant breaks a prompt into several related searches, often called fan-out queries, and writes its answer from what those searches return. A ranking for the main query covers part of that. In Ahrefs’ study of 15,000 long-tail prompts, 12% of the links cited by ChatGPT, Gemini and Copilot appeared in Google’s top 10 for the same prompt, and more than 80% of their citations came from pages that did not rank for it at all [3]. Google’s AI Overviews sit closer to its rankings: in a second Ahrefs study, 38% of AI Overview citations came from the top 10 [4].
The engines
Each assistant chooses and fetches its sources its own way. In the same study, 28.6% of Perplexity’s citations ranked in Google’s top 10, more than double the others [3]. ChatGPT’s search features find pages through OpenAI’s own crawler, OAI-SearchBot, and OpenAI recommends allowing it in robots.txt [5]. Crawler access, in robots.txt and at the CDN, becomes a checklist with one line per engine.
The scoreboard
Visibility in AI answers is measured in mentions, citations and share of voice across a fixed set of prompts, plus the referral sessions those answers send. The platforms have started to report it: in February 2026 Bing Webmaster Tools added an AI Performance report that shows how a site’s content is cited across Microsoft Copilot, AI-generated summaries in Bing and partner integrations [6].
AEO, GEO and SEO side by side
| SEO | AEO | GEO | |
|---|---|---|---|
| Goal | A position in the results list | A citation inside the answer | A passage the engine retrieves and quotes |
| Where it shows | Google and Bing results | ChatGPT, Perplexity, Gemini, Copilot, AI Overviews, AI Mode | The same engines as AEO |
| Unit of success | The page | The passage | The passage |
| Main signals | Relevance, links, technical health | Entities, structure, authority on the topic | Coverage of the related searches, specifics a model can quote |
| Measured by | Rankings, clicks, organic sessions | Citations, share of voice, AI referral sessions | The same as AEO |
How I run AEO, GEO and SEO as one program
I run the three as one program because each part feeds the next. The SEO foundation makes the site retrievable. The keyword research grows into a map of the questions behind each topic: main keywords for the core intent and satellite keywords for the supporting questions an assistant searches, so the fan-out is covered. Entity and schema work closes the gaps between what a model knows about the brand and what the brand does. Digital PR and link building earn the mentions on other trusted sites. Tracking reports rankings, citations and share of voice side by side, every month.
On one program, a FinTech comparison brand working across 26 markets went from 14 to more than 160 answers citing it in AI Overviews and assistants, and its AI-assistant referral sessions grew from under 500 to 18,000 a month. There are more results in my case studies. How a program runs month by month is on my SEO consulting page.
A worked example: one topic, three lenses
The numbers here are illustrative. Take a payroll software brand and the topic of paying contractors abroad.
The SEO lens looks at a page that ranks for “pay international contractors”, with the links and technical health to hold its position.
The AEO lens starts from the prompts a buyer gives an assistant, such as “what is the best way to pay contractors in five countries”, and checks whether the answer names the brand. Across 40 such prompts in four engines, the brand is named in 12 of 160 answers, a 7.5% share of voice.
The GEO lens looks at the searches behind those answers: tax forms by country, currency fees, payment timing and compliance. The brand’s page answers two of the four. The program’s first jobs follow from that: a passage for each missing question on the pages that cover the topic, entity work so the engines connect the brand with contractor payroll, and mentions on the comparison sites the answers already cite.
Frequently asked questions
Is GEO the same as AEO?
They describe the same goal from two sides. AEO starts from the answer and asks whether the brand is in it; GEO starts from retrieval and asks how a generative engine picks and quotes its sources. In practice the work is one program.
Does SEO still matter for AI search?
Yes. Assistants find their sources through search indexes and their own crawlers, and Google says the best practices for SEO remain relevant for AI Overviews and AI Mode. SEO is the foundation the citations stand on.
What is LLMO?
LLM optimization: a third name for the work of getting a brand named in AI answers, with the emphasis on the language models behind the assistants. It covers the same ground as AEO and GEO.
Do I need a separate team for AEO, GEO and SEO?
One team can run all three, because they share the research, the content and the authority work. Splitting them tends to produce three plans for one website.
How do I measure AEO, GEO and SEO together?
Report rankings and organic sessions next to mentions, citations and share of voice for a fixed set of prompts, plus AI referral sessions in analytics. Search Console counts Google’s AI features inside its Web search data, and Bing Webmaster Tools reports citations in Copilot.
Sources
- Pranjal Aggarwal and others, “GEO: Generative Engine Optimization”, arXiv, first submitted 16 November 2023 (accepted to KDD 2024). arxiv.org
- Google Search Central, “AI features and your website”, last updated 10 December 2025. developers.google.com
- Ahrefs, “Only 12% of AI Cited URLs Rank in Google’s Top 10 for the Original Prompt”, 11 August 2025. ahrefs.com
- Ahrefs, “Update: 38% of AI Overview Citations Pull From The Top 10”, 2 March 2026. ahrefs.com
- OpenAI, developer documentation on OpenAI’s crawlers, undated, read 11 October 2026. developers.openai.com
- Microsoft Bing, “Introducing AI Performance in Bing Webmaster Tools Public Preview”, 10 February 2026. blogs.bing.com