Artificial Intelligence In Supplier Selection And Performance Monitoring: A Framework For Supply Chain Managers

Abstract

The use of AI to supply chain management is the subject of this research, which zeroes in on two areas: supplier evaluation and performance tracking. The research used a PRISMA-based systematic methodology to systematically review pertinent literature from the Web of Science database, ensuring rigor by filtering out papers without clear inclusion and exclusion criteria. We looked at AI supply chain management apps that used important methods like ML, DL, and predictive analytics. Research into the function of AI has grown substantially over the last decade, according to the findings. This is especially true in domains connected to suppliers, like quality control, cost optimization, and risk management. The geographical distribution of the studies also shows that North America and Europe have made significant contributions to the field, while Asia is starting to make its mark. Better supplier selection and performance monitoring are both made possible by utilizing AI, and these insights lay the groundwork for this to happen for supply chain management.