OPTIMIZING SUPPLY CHAIN EFFICIENCY IN THE MANUFACTURING SECTOR THROUGH AI-POWERED ANALYTICS

Abstract

The integration of AI-powered analytics offers transformative potential in optimizing supply chains within the manufacturing sector. This study adopts a qualitative, case study methodology to explore the specific ways manufacturers utilize AI-powered solutions in areas such as demand forecasting, inventory management, logistics planning, and predictive maintenance. Findings indicate substantial gains in efficiency, cost savings, and improved supply chain resilience. Additionally, the study highlights how AI-driven optimizations lead to an enhanced customer experience through increased product availability, reduced lead times, and a more responsive supply chain. Through detailed analysis of real-world implementations, the study provides practical guidance for manufacturers seeking to leverage AI to transform their supply chain operations.