Optimizing Supply Chain Performance Using AI and Machine Learning: A Predictive Analytics Approach
DOI:
https://doi.org/10.71143/n5d6fr98Keywords:
Artificial intelligence, Supply Chain Optimization, Machine Learning, Predictive analytics, LogisticsAbstract
The paper presents the manner in which AI and ML have reshaped supply chain management (SCM) by making demand predictions, controlling inventory, reducing logistics costs, and controlling risks. It points out the opportunities of predictive analytics in enhancing the performance of supply chains in different industries. The paper analyses cases to demonstrate the efficiency benefits that AI/ML can bring as well as discuss some of the challenges, like those of quality and scalability of data and scalability and compatibility of systems. Although the process of implementing AI/ML can make the operations more efficient, it is expensive and necessitates clear planning and technological and people resources. The paper established that AI and ML have significant potential to provide businesses with a competitive advantage in the new global economy.
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