Strategic use of artificial intelligence in enterprise supply chain management

Abstract

This study analyzed the strategic use of artificial intelligence (AI) in supply chain management to optimize efficiency, accuracy, and decision-making. A comprehensive review of academic literature and relevant business case studies was conducted to assess the impact of AI on logistics process optimization, decision-making, and operational efficiency within the supply chain. Analytical, inductive, and deductive methods were applied to critically break down and examine the collected information. The results revealed that the implementation of AI brings significant benefits. For example, Lithuanian trade company Maxima has successfully reduced inventory levels by 20% and improved sales forecast accuracy by 15% through AI-driven demand prediction systems. Similarly, another company Eugesta has experienced a 30% reduction in inventory levels and a 20% improvement in sales forecast accuracy due to AI algorithms. Building on this research, the authors propose a model that integrates AI-driven supply chain optimization strategies, outlining key factors for enhancing business efficiency, predictive accuracy, and decision-making. The proposed model aims to serve as a structured framework for companies looking to leverage AI for sustainable competitive advantage in supply chain management.