This study explores the role of artificial intelligence (AI) in enhancing omnichannel customer experience within retail e-commerce through a cross-case analysis of three prominent retailers: Amazon, Walmart, and Sephora. As omnichannel retailing becomes central to meeting evolving consumer expectations, AI-driven innovations like recommendation systems, chatbots, and predictive analytics are increasingly utilized to create seamless, personalized shopping experiences. Each case highlights distinct strategies and AI applications tailored to its business model: Amazon leverages AI for personalization and operational optimization across its vast digital ecosystem; Walmart emphasizes AI in inventory management and in-store technology to bridge physical and digital channels; and Sephora uses AI-driven tools to enhance customer engagement and personalization in beauty retail. Findings reveal shared themes in AI’s impact on customer satisfaction and operational efficiency, while also identifying challenges related to data integration, consistency across channels, and resource allocation. The study contributes valuable insights into best practices and emerging trends in AI-driven omnichannel retail, providing a foundation for further research on AI’s potential to redefine customer experiences and retailer performance.