Leveraging AI and Machine Learning in Modern Supply Chain Management: An Evaluation of Technological Adoption and Performance Impact


  • Yu Chen World link US, Frisco, Texas, USA


Modern Supply Chain Management, Machine Learning, Artificial Intelligence


In this study, the revolutionary potential of artificial intelligence (AI) and machine learning (ML) in contemporary supply chain management is examined, along with the effects of these technologies on performance. The purpose of this study is to fully comprehend the adoption of AI and ML, its uses, and its effects on supply chain operations.The first section of the study is a thorough survey of the existing literature on supply chain management using AI and machine learning. In-depth interviews with industry professionals are combined with quantitative survey data to produce qualitative insights. The data analysis involves both statistical techniques and thematic analysis. Quantitative data are analyzed using regression and correlation analysis to explore the relationship between AI and ML adoption and supply chain performance metrics. The research contributes to the theoretical understanding of technology adoption in supply chain management, enriching existing frameworks related to technology acceptance, supply chain performance, and risk management. This research emphasizes the critical role of AI and ML in shaping the future of supply chain management. Embracing AI and ML today is the key to unlocking the potential of a technologically advanced and future-proof supply chain.


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How to Cite

Chen, Y. . (2024). Leveraging AI and Machine Learning in Modern Supply Chain Management: An Evaluation of Technological Adoption and Performance Impact. International Journal of Intelligent Systems and Applications in Engineering, 12(14s), 457–467. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4681



Research Article