GEO (Generative Engine Optimization)
Also known as: Generative Engine Optimization
GEO is the academic term for optimizing content so that generative AI engines surface and cite it in their synthesized answers.
GEO was popularized by a 2023 Princeton / Georgia Tech / IIT Delhi paper that proposed the term and benchmarked techniques for influencing what large language models cite. The paper found that adding statistics, quotations, and authoritative citations to a page meaningfully increased its visibility in generative answers.
In practice GEO, AEO, and AgenticSEO describe the same problem: getting cited by AI. GEO emphasizes the content-craft side (what the prose contains), AEO emphasizes the structural side (schema, FAQ blocks), and AgenticSEO emphasizes the operational side (continuous measurement and metadata generation).
Related terms
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