GEO vs AEO: What's the Difference?

Answer Engine Optimization (AEO) is generally used for optimizing toward structured, answer-format search features - featured snippets, knowledge panels, and Google's AI Overviews - aiming to become the explicit, extractable answer a search engine returns directly.

Generative Engine Optimization (GEO) is generally used for optimizing toward being cited or referenced inside the free-form responses generated by conversational AI tools like ChatGPT, Claude, and Perplexity - less about a specific answer box, more about being the source those tools draw on and mention when generating a reply.

Terminology in this space hasn't fully settled, and it's worth knowing both readings exist. Some practitioners draw a real distinction: AEO for earning a fixed, structured slot in a search engine's own answer feature, GEO for earning a mention inside an AI's generated, conversational output - different surfaces with somewhat different content requirements even though the underlying groundwork overlaps heavily. Other practitioners treat GEO and AEO as effectively the same discipline described by two different terms that emerged around the same time, since both are ultimately about the same core work: structuring content clearly enough, and establishing enough credibility, that an AI system - whether it's producing a snippet or a full generated answer - chooses to surface it. Regardless of which framing a given source uses, the practical foundation for both is largely the same as it is for AEO on its own: direct, well-structured answers, clear expertise and citations, and content built to be easily extracted rather than requiring a click to make sense of.