AI-Enhanced Supply Chain Optimization: A Study of Indian E-Commerce Sector

Abstract

This paper investigates the role of Artificial Intelligence (AI) in optimizing supply chains in India's rapidly growing e-commerce sector. AI-powered algorithms such as Machine Learning (ML) and Reinforcement Learning (RL) are increasingly being deployed to enhance supply chain efficiency by predicting demand, optimizing inventory, and improving last-mile delivery. The study analyzes the performance of AI models like Decision Trees, Random Forest, and Deep Q-Networks (DQN) in supply chain management, focusing on real-time decision-making capabilities and cost reduction. Case studies from leading Indian e-commerce companies, including Flipkart and Amazon India, are presented to demonstrate the impact of AI on reducing operational inefficiencies and improving customer satisfaction. The research also explores the challenges of implementing AI in supply chain operations in India, including data integration issues, infrastructure limitations, and workforce adaptation to AI technologies. Finally, the paper discusses future trends in AI-driven supply chain management, such as autonomous vehicles and drone deliveries, which hold immense potential in the Indian context.