Semantic Search refers to the process by which search engines—and increasingly AI models—understand the meaning behind query terms, rather than simply matching literal keywords. Instead of treating words as isolated tokens, semantic search systems analyze context, intent, and the conceptual relationships among words (often via embeddings, knowledge graphs, and Natural Language Understanding). In practice, that means the engine infers what users really want—interpreting synonyms, related entities, user history, and question-answer patterns—to surface results that satisfy the underlying concept rather than just a string match. For AI SEO, mastering semantic search means structuring content and markup so that LLM-powered retrieval systems “get” your page’s topic and relevance at a conceptual level, ensuring you show up when AI agents stitch together answers from across the web.