AI-Based Intelligent Supply Chains: Theoretical Exploration and Prospects

Abstract

With the emergence of artificial intelligence (AI), supply chains are transitioning from traditional operating models to intelligent and data-driven systems. An AI-based intelligent supply chain is an advanced integrated technology and management system built on AI and machine learning, which achieves intelligence, networking, collaboration, integration, and automation. By combining human expertise with machine capabilities, these supply chains are evolving into autonomous systems that are capable of self-awareness, self-direction, and self-optimization, with resilience and sustainability as their objectives. AI-based intelligent supply chains increasingly depend on AI and machine learning to automate decision-making processes. By integrating advanced technologies such as AI, the Internet of Things, and big data, these systems are able to monitor and analyze each link of the supply chain in real time and promptly detect emerging issues and risks. The effectiveness of these systems hinges on development on both the supply and demand sides. On the supply side, organizational structure, process integration, and the coordination of key elements form the foundation for effective use of AI. On the demand side, users’ cognitive, emotional, and functional recognition regarding AI are central determinants of its actual effectiveness. Ultimately, it is the alignment between supply and demand that shapes the performance of AI-based intelligent supply chains. The governance of these systems requires a hybrid approach that seamlessly integrates contractual, relational, and algorithmic mechanisms, with the extent of each varying by context.

Keywords

artificial intelligence (AI) / AI-based intelligent supply chain / supply and demand perspectives / hybrid governance mechanism / theoretical exploration and prospects

RIGHTS & PERMISSIONS

Higher Education Press