A Canonical Map is the structured framework that defines how a brand’s entities, identifiers, and knowledge assets interrelate within its digital ecosystem. It acts as the connective tissue between canonical identifiers, showing how people, organizations, concepts, and frameworks link together through verifiable relationships. In AI Search Optimization, a canonical map ensures that large language models (LLMs) can correctly interpret and traverse these relationships—improving entity disambiguation, factual consistency, and citation accuracy across AI-generated answers. Essentially, it serves as the brand’s semantic blueprint, aligning human-readable content with machine-readable structure for maximum discoverability and authority.