AI and Big Data Analytics for Demand-Driven Supply Chain Replenishment

Abstract

The increasing complexity and volatility of global supply chains have necessitated the adoption of advanced technologies such as Artificial Intelligence (AI) and Big Data Analytics to improve supply chain efficiency, accuracy, and responsiveness. One of the critical aspects of supply chain management is inventory replenishment, where timely and accurate demand forecasting is essential for minimizing stockouts, reducing excess inventory, and enhancing overall operational efficiency. AI and Big Data Analytics offer significant advantages in demand-driven supply chain replenishment by enabling real-time data processing, advanced forecasting models, and automated decision-making processes. This research article explores the integration of AI and Big Data Analytics in demand-driven supply chain replenishment systems, their applications, benefits, challenges, and future prospects. By examining case studies and key technologies, this paper highlights the transformative potential of these technologies in optimizing supply chain operations.