Generative Engine Optimization (GEO)
Generative engine optimization is the practice of optimizing content to be cited in AI-generated answers, an alternative name for AEO that emphasizes the generative engines producing the responses.
Also known as: GEO
Generative engine optimization is AEO under a different name. GEO and Answer Engine Optimization describe the same goal — getting your content surfaced and cited by AI systems that generate answers rather than list links. GEO foregrounds the generative engines (ChatGPT, Gemini, Perplexity); AEO foregrounds the answer they produce. In practice the disciplines are the same.
Whatever you call it, the work is identical and maps onto the AEO Canon: be readable by crawlers, answer the real questions, write extractable passages, and earn the authority and credibility that get you cited. The terminology varies across the industry, so it's worth recognizing GEO, AEO, "AI SEO," and "LLM optimization" as largely interchangeable labels for optimizing toward citation in answer engines. The core mechanism remains making your passage the best, most liftable answer — the extractability pillar.
Example. A team that says it's "doing GEO" and one that says it's "doing AEO" are running the same playbook — tracking share of voice across engines and improving the pages that aren't yet getting cited.
Relevant pillar
Related terms
- Answer EngineAn answer engine is a search system that responds to a question with a direct, synthesized answer instead of a list of links, usually citing the sources it drew from.
- Share of Voice (AI)Share of voice in AI search is the proportion of relevant AI answers in which your brand appears, measured across a fixed set of questions, as a gauge of how present you are in the conversation.
- RAG (Retrieval-Augmented Generation)RAG is the technique behind most AI answer engines, where the model first retrieves relevant documents from the live web or an index and then generates an answer grounded in what it found.