Artificial Intelligence (AI) is revolutionizing the retail industry, particularly in e-commerce, by enhancing search capabilities through technologies like natural language processing, image recognition, and data analysis. Traditional keyword-based search mechanisms often struggle to handle the nuanced and voluminous data e-commerce generates, leading to the rise of vector search, which uses AI-driven algorithms to understand relationships between data points and improve search accuracy. Vector search overcomes the limitations of keyword matching by using mathematical techniques to retrieve items that are semantically similar to user queries, even without exact keyword matches, enabling more intuitive and contextual search experiences. Such advancements allow retailers to personalize search results, increasing customer satisfaction and transaction success rates. To implement these advanced search capabilities, retailers must address challenges like data overload and changing consumer behavior, which can be managed using tools like MongoDB Atlas Vector Search, offering a robust and scalable solution for real-time responsiveness and enhanced customer engagement in e-commerce.