AI embeddings and semantic search explained for product managers

Understanding AI embeddings is essential for product managers building modern search. Learn how text embeddings move beyond strict keyword matching to deliver results based on actual meaning. Think of a spice rack sorted by taste rather than alphabetically. This lesson uses that metaphor to explain how embedding models plot words in a multidimensional space. The AI measures the distance between concepts to understand context, grouping related ideas even if the words differ. We apply this to an e-commerce scenario where a user searches for a comfy couch and the system returns a soft loveseat. You do not need to build the math, but you must guide the product and evaluate engineering work with vector databases. In this lesson: - The spice rack metaphor for semantic search - Plotting text in thousands of invisible dimensions - E-commerce examples of matching user intent - Steps to audit search logs and zero-result rates U2xAI Academy - AI skills for product managers.