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Generative engine optimization
Process of improving visibility in generative AI systems From Wikipedia, the free encyclopedia
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Generative engine optimization (GEO) is the process of improving the visibility, relevance, and presentation of content in response to queries made to generative engines, such as large language models (LLMs).
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Unlike SEO, which targets traditional search engine rankings, GEO focuses on how information is surfaced, summarized, or cited by artificial intelligence systems powered by generative models.[1]
"Generative engine optimization" is not yet a universally accepted name. It is also referred to as "answer engine optimization" (AEO)[2], "artificial intelligence search optimization"[3] or artificial intelligence optimization.
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History
The concept of generative engine optimization emerged in the early 2020s alongside the widespread adoption of generative AI tools such as OpenAI's ChatGPT, Anthropic's Claude, and Google's Gemini.[1]
Industry applications
- Marketing: Brands aim to influence how their offerings are presented in AI‑generated summaries or product recommendations.[1]
See also
References
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