Model-aware schema is a concept in technical SEO and AEO that refers to the practice of authoring structured data markup with the explicit goal of making content easier for large language models and AI search systems to parse, interpret, and cite, rather than solely optimising for traditional search engine rich results. While standard Schema.org vocabulary such as Article, FAQPage, HowTo, and Product was originally designed to help crawlers understand page content and generate SERP features, model-aware schema goes further by emphasising precision in entity labelling, explicit relationship declarations, and the use of properties that map to concepts an LLM is likely to query against. As AI search systems increasingly use structured data as a retrieval signal, the gap between schema written for Googlebot and schema written to ground model responses is becoming a meaningful distinction in advanced technical SEO practice.