The incorporation of Generative Artificial Intelligence (GenAI) in real-time dashboard systems is revolutionizing the working environment of retail supply chains. This paper presents an in-depth study of GenAI-enabled dashboards that optimize the end-to-end supply chain by processing real-time data, providing predictive analytics, and enabling fast, intelligent visualization. By addressing the issues of stockouts, inefficient lead times, and checkout delays, the paper explores how streaming information directly provided by systems such as point-of-sale systems, IoT sensors, and inventory platforms can be analyzed in real time using powerful AI models to deliver practical solutions when needed. It also describes the architecture of these systems and emulates their impact on supply chain visibility, adaptability, and customer experience. Within the given paper, it is possible to determine the fundamental deficiencies of current literature and/or practice (specifically, poor utilization of GenAI towards interactive, operational settings). Evidence suggests that combining explainable AI, automation, and user-centered design is critical to facilitating more rapid decision-making, strategic fit, and a competitive edge in the contemporary retail setting.
Keywords: AI dashboards, GenAI, Real-time Analytics, Supply chain visibility, checkout automation, streaming
