Generative engine optimization

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 web search rankings, GEO focuses on how information is surfaced, summarized, cited, or directly generated by artificial intelligence systems powered by generative models.

GEO involves techniques that help content creators, publishers, and organizations shape how their data, branding, and narratives are represented in AI-generated responses. According to *On Marketing*, "Generative Engine Optimization (GEO) is the practice of tailoring content and structure to maximize visibility and usefulness within AI-generated search and recommendation results."

As generative AI becomes increasingly integrated into consumer tools, productivity software, search interfaces, and digital assistants, optimizing for these systems has become a growing concern for marketers, educators, and developers.

Industry applications

• Marketing: Brands aim to influence how their offerings are presented in AI‑generated summaries or product recommendations.
• Education: Institutions seek accurate representation in AI‑powered tutoring systems and summarization tools.
• Law and policy: Legal professionals and policymakers monitor how statutes, regulations, or case law are interpreted by AI assistants.

See also

• Large language model
• Artificial intelligence
• Prompt engineering
• Machine learning
• Natural language processing
• Search engine optimization
• Algorithmic bias