In the rapidly evolving landscape of e-commerce, visual search has emerged as a transformative technology, enabling users to discover products through images rather than text-based queries. Powered by artificial intelligence (AI), machine learning, and computer vision, visual search enhances the shopping experience by offering more intuitive, accurate, and efficient product discovery. This paper explores the growing significance of visual search in e-commerce, highlighting its role in improving search relevance, personalization, and customer engagement. It examines the underlying AI-driven technologies, such as deep learning-based image recognition, and their impact on enhancing product recommendations and reducing search friction. Additionally, the study discusses the competitive advantages of retailers adopting visual search, including increased conversion rates and improved customer satisfaction. Challenges such as data privacy concerns, technological limitations, and implementation costs are also addressed. By leveraging AI-driven visual search, e-commerce platforms can redefine how consumers interact with online retail, bridging the gap between inspiration and purchase.