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The rationale and paradigm for integrating artificial intelligence (AI) into pharmaceutical procurement systems are examined in this study. Through an analysis of the existing status of medicine procurement, we pinpoint important areas where artificial intelligence could improve process accuracy, efficiency, and dependability. It is advised to use AI to automate ordering, forecast demand, maximize inventory, and assess supply chain hazards. It is possible to determine whether certain AI models can improve medicine procurement procedures by testing and assessing them. By putting these models into practice and continuing to monitor and optimize them, drug procurement systems can lower the risk of shortages, manage inventories more effectively, and save money over the long run. This paper offers a framework for a methodical approach to process optimization and performance enhancement when integrating AI into pharmaceutical procurement systems.
Milićević et al. (Mon,) studied this question.