AI Answer Optimization is the practice of engineering a brand’s digital assets—content, schema, and knowledge signals—so they are more likely to be retrieved, cited, or recommended within AI-generated answers from large language models (LLMs) such as ChatGPT, Claude, Gemini, and Perplexity. Unlike traditional SEO, which targets search engine rankings, AI Answer Optimization focuses on retrieval relevance and citation probability within generative systems. It involves structuring machine-readable context, strengthening entity authority, and aligning content semantics with the embedding patterns LLMs use to surface authoritative responses.