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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).

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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