This article examines the transformative impact of Event Driven Architecture (EDA) on retail inventory management. As consumer expectations shift toward omnichannel fulfillment and immediate availability, traditional batch processing approaches increasingly fail to meet market demands. It explores how EDA reimagines inventory management through real time event processing, enabling continuous visibility and automated decision making across complex supply networks. It investigates the stream processing technologies powering these systems, primarily Apache Kafka and Apache Flink, alongside the integration of artificial intelligence for predictive capabilities and automated inventory decisions. Through analysis of implementation patterns, it demonstrates how EDA creates more responsive, resilient, and efficient retail supply chains that simultaneously improve product availability, reduce inventory costs, and enhance customer experiences. Despite implementation challenges related to legacy systems, data quality, and organizational change management, EDA adoption represents a strategic necessity for retailers navigating increasingly complex market conditions. The article suggests that retailers implementing EDA gain competitive advantages through improved accuracy, responsiveness, and the ability to break traditional tradeoffs between inventory efficiency and product availability.
Keywords: Artificial Intelligence, event-driven architecture, retail inventory management, stream processing, supply chain optimization
