Generative engine optimization (GEO)
Also called GEO, AI search optimization, answer engine optimization, AEO, LLM SEO
Making your content easy for AI answer engines like ChatGPT search, Perplexity and Google AI Overviews to find, understand and cite.
Generative engine optimization is the practice of making content more likely to be used and cited in AI-generated answers. Answer engines retrieve web pages, pull relevant passages, and generate a response, often with source links. GEO is about being one of those sources, alongside traditional SEO, which is about ranking in a list of links.
Much of GEO overlaps with good SEO and good writing. Content that answers questions directly, states facts clearly with dates and sources, uses descriptive headings, and is technically accessible to crawlers tends to do well in both. Specific to AI retrieval: passages should make sense on their own, because engines quote sections, not whole pages. Clear definitions, comparison tables, specific numbers and named expertise make passages more useful to quote.
GEO is a young field with few proven tactics, and claims of guaranteed AI rankings deserve scepticism. Measurement is hard because AI answers vary and many tools do not report referrals clearly. Practical steps include checking how AI tools currently answer questions in your field, allowing reputable AI crawlers in robots.txt if you want to be cited, and publishing an llms.txt file.
Example
A travel insurance company rewrites its claims page so each common question has a heading phrased as the question and a 50-word direct answer underneath. Within a few months, AI answer engines begin citing those passages for questions like "how long do travel insurance claims take".
Common mistake
Chasing AI visibility with tricks such as hidden text, keyword stuffing or content written only for bots. These tend to backfire and harm human readers. Content that is clear, specific and trustworthy for people is also what AI systems are designed to prefer.