People increasingly get answers from ChatGPT, Perplexity, Gemini and Google's AI Overviews instead of clicking ten blue links. Generative Engine Optimization (GEO) is the practice of getting your content cited in those AI answers. It overlaps heavily with SEO but isn't identical — here's the practical version.
What GEO is
GEO is optimizing your content to be surfaced and cited by AI answer engines. Where classic SEO aims for a ranking position you click, GEO aims to be one of the sources an LLM synthesises its answer from — and ideally the one it links. The goal shifts from "rank" to "get quoted".
GEO vs SEO
The good news: the foundations are shared. AI engines lean heavily on the same signals — crawlable content, clear structure, topical authority, and trust. The differences are emphasis: AI engines reward content that directly answers a question, is easy to extract in self-contained chunks, and carries clear authorship and citations. GEO is less about keywords and more about being the clearest, most quotable source on a topic.
How AI engines pick sources
Most AI answer engines retrieve candidate sources (often from a search index), then synthesise an answer and cite some of them. So being findable by conventional search is still step one — if Google can't crawl or index you, the AI layer usually can't cite you either. From there, they favour sources that answer the specific query cleanly and read as authoritative.
Practical tactics
What actually helps: write clear, self-contained answers near the top of the relevant section (the inverted-pyramid style); use descriptive headings that mirror real questions; add specifics — data, dates, named entities — that models latch onto; keep authorship and trust signals visible; and make sure you're technically crawlable in the first place.
llms.txt and structured content
Two structural aids. llms.txt is an emerging file that gives AI assistants a curated map of your site's key content. And clean structured data helps machines parse what your page is about. Neither is a silver bullet, but both reduce the friction between your content and the model trying to understand it.
Measuring AI visibility
This is still immature. Practical signals: referral traffic from AI tools in your analytics, manually testing whether the engines cite you for your target questions, and watching for AI-Overview appearances in Search Console as reporting matures. Meanwhile, the surest foundation is the same technical health SEO always needed — SEO Inspector keeps your pages crawlable, well-structured and trustworthy, which is exactly what the AI layer reads too.
