An Integrated AI-Power BI Model for Real-Time Supply Chain Visibility and Forecasting: A Data-Intelligence Approach to Operational Excellence

In today’s dynamic and complex business landscape, achieving real-time visibility and accurate forecasting in supply chain operations is essential for sustaining competitiveness and operational excellence. This study proposes an integrated Artificial Intelligence (AI) and Power BI model designed to enhance real-time supply chain visibility and predictive capabilities through a data-intelligence-driven approach. The framework leverages machine learning algorithms for demand forecasting, anomaly detection, and performance optimization, while utilizing Power BI’s robust data visualization and dashboarding functionalities to offer intuitive insights for decision-makers. The model integrates disparate data sources across procurement, inventory, logistics, and sales channels, transforming raw data into actionable intelligence. Through AI-based predictive analytics, the system forecasts demand patterns, identifies potential disruptions, and prescribes adaptive strategies to optimize resource allocation and reduce lead times. Furthermore, the Power BI component ensures dynamic, user-friendly dashboards that allow supply chain managers to monitor key performance indicators (KPIs), track supplier performance, and assess inventory levels in real-time. To validate the model, a case study was conducted in a mid-sized manufacturing enterprise, where the implementation of the AI-Power BI model led to a 27% improvement in forecasting accuracy, a 19% reduction in stockouts, and a 22% increase in supply chain responsiveness. The real-time data pipeline also enhanced collaboration across departments, resulting in more agile and informed decision-making. This research highlights the significance of integrating AI technologies with business intelligence platforms to overcome traditional supply chain inefficiencies. It contributes to the growing body of knowledge on Industry 4.0 by offering a scalable, adaptable solution that aligns with digital transformation goals. The proposed model empowers organizations to transition from reactive to proactive supply chain management, fostering agility, resilience, and data-driven culture. Future work will focus on incorporating blockchain for enhanced transparency and leveraging edge computing to improve data processing latency. The integrated AI-Power BI model is poised to revolutionize supply chain management by enabling smarter forecasting and end-to-end visibility.