Generative Engine Optimization (GEO)
Generative Engine Optimization (GEO) is the practice of shaping content so AI chatbots like ChatGPT, Gemini, and Perplexity cite or recommend it when they generate an answer, rather than optimizing for a ranked list of links.
Also known as: Generative Engine Optimization
Generative Engine Optimization is the work of making your business easy for an AI system to find, understand, and name when it generates an answer instead of a ranked list of links. That includes what you publish (pricing pages, service pages, real project details), where you're listed (directories, review sites, your own domain), and how clearly a model can extract facts about who you are and what you do.
You'll also see this called AEO (answer engine optimization) and LLMO (large language model optimization). Honestly, the three terms describe the same underlying practice, and the industry hasn't settled on one name. Don't spend time trying to find a crisp line between them. If someone tells you GEO and AEO are different disciplines with different playbooks, be skeptical.
GEO differs from classic SEO in what it's optimizing for. SEO earns a ranking position on a search results page. GEO earns a mention inside a generated answer, and that answer might name two or three companies instead of ten blue links. Ahrefs found that the share of AI Overview citations coming from pages that also rank in Google's top 10 organic results fell from 76% to 38% between July 2025 and March 2026, which means ranking well on Google no longer guarantees you show up in the AI answer built from that same query.
One thing GEO does not mean: adding schema.org markup and expecting citations to follow. The one empirical test of that idea, run by Search Atlas, found no correlation between schema coverage and how often LLMs cited a site. Schema can still help classic search engines index your pages correctly, and that indexing feeds the retrieval systems some answer engines use, but no one has shown that markup alone earns you a citation.
Keep exploring the glossary
- Answer Engine Optimization (AEO)Answer Engine Optimization (AEO) is the practice of structuring content so answer engines such as ChatGPT, Perplexity, and Google's AI Overviews can extract a direct answer from it and attribute that answer to your business.
- Large Language Model Optimization (LLMO)Large Language Model Optimization (LLMO) is the practice of making content easy for a large language model to retrieve, understand, and repeat accurately, so it names your business when answering a customer's question.
- AI VisibilityAI visibility is how consistently a business gets named when AI systems like ChatGPT, Gemini, and Perplexity answer a customer's buying question, measured across repeated prompts and multiple engines rather than a single check.
- Citation (AI answer)In an AI answer, a citation is a source the engine references or links to while generating its response, and the number of sources cited per answer varies widely by engine, from about 2.5 for Copilot up to about 7.7 for Google AI Overviews.
Common questions about Generative Engine Optimization (GEO)
- Is GEO different from AEO or LLMO?
- Not in any way the industry agrees on. GEO, AEO, and LLMO all describe getting cited or recommended by AI systems. Treat them as synonyms until a clearer distinction emerges.
- Does GEO replace SEO?
- No. Search still sends far more traffic than AI answer engines do, AI platforms account for roughly 0.32% of all website traffic as of 2026 versus about 42.75% from organic search, according to Similarweb-family data. GEO is additive work, not a replacement.