AIoT-Driven Business Intelligence and Supply Chain Optimization: Real-Time Insights for Strategic Decision-Making and Sustainable Operations

This research introduces a comprehensive framework for integrating Artificial Intelligence of Things (AIoT) into modern supply chain management. We examine five AIoT-enabled applications: dynamic fleet routing, supplier risk monitoring, autonomous inventory replenishment, Just-in-Time (JIT) delivery optimization, and warehouse robotics coordination. Synthetic datasets and machine learning models—ranging from regression to classification and reinforcement learning—simulate predictive scenarios for each domain. Our findings underscore measurable improvements in delivery efficiency, risk mitigation, and sustainability. This study demonstrates how AIoT facilitates real-time decision-making, enhances resilience, and fosters eco-conscious operations in complex supply chain ecosystems.