Transforming Supply Chain Efficiency: The Integration of Real-Time Inventory Tracking and AI-Powered Demand Forecasting

Authors

  • Narendranath Yenuganti Mudrasys Inc., USA Author

DOI:

https://doi.org/10.32628/CSEIT25112491

Keywords:

Supply chain optimization, real-time inventory tracking, AI-powered demand forecasting, digital transformation, predictive analytics

Abstract

This article explores the transformative impact of integrating real-time inventory tracking and AI-powered demand forecasting on supply chain efficiency. The synergistic combination of these technologies enables organizations to create intelligent, responsive supply chains that continuously optimize operations. Real-time inventory tracking provides unprecedented visibility across multiple locations and channels, while AI-driven demand forecasting incorporates diverse variables beyond historical sales data to predict future needs with remarkable precision. Together, these technologies enable dynamic inventory optimization, proactive replenishment, efficient resource allocation, reduced safety stock requirements, and enhanced supplier collaboration. The business impact spans multiple dimensions, including reduced inventory carrying costs, improved service levels, working capital optimization, increased order fulfillment accuracy, and overall supply chain cost reductions. As these technologies evolve, they promise even greater integration with production planning, transportation management, and customer relationship management systems, creating unified digital ecosystems. Organizations embracing this technological transformation can achieve sustainable competitive advantage through supply chains that not only respond to market changes but anticipate them.

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Published

16-03-2025

Issue

Section

Research Articles