Generative
Engine
Optimization.
The discipline of making a brand citeable by ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude and Copilot.
Definition. Generative Engine Optimization (GEO) is the practice of structuring a brand's content, entities and citation sources so that large language models and AI-powered search engines reliably cite that brand when generating answers to buyer questions.
Etymology
The term was introduced to describe the optimization discipline emerging around generative AI search engines in 2023–2024, as ChatGPT, Perplexity, Google AI Overviews and similar systems began generating answers from cited sources rather than returning ranked link lists. GEO contrasts with Answer Engine Optimization (AEO), which refers to the narrower on-page execution layer.
What GEO covers
A GEO engagement typically includes entity disambiguation, schema and structured-data architecture, question-first content design, citation-source strengthening (Wikidata, Wikipedia, high-authority publications), and continuous measurement of brand share-of-voice across multiple AI answer surfaces.
Why it matters
When an AI answer engine generates a response, it typically draws from a small number of trusted sources. Brands that are inside that source pool become the shortlist. Brands that aren't become invisible — regardless of how well they rank in classical Google.
Related terms
Further reading
→ What is Generative Engine Optimization? (pillar article)
→ GEO vs SEO: the difference that matters
→ Our GEO service page
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