With the rapid development of artificial intelligence technology, its application in supply chain management has gradually become an important means to improve efficiency and optimize decision-making. This study focuses on supply chain logistics prediction and decision optimization driven by artificial intelligence, analyzing the application of artificial intelligence technologies such as machine learning, deep learning, and data mining in the logistics field. Through research on demand forecasting, inventory management, transportation scheduling, and other aspects, this article finds that artificial intelligence can effectively improve the accuracy of forecasting, optimize the decision-making process, thereby reducing costs, improving response speed, and enhancing the flexibility of the supply chain. At the same time, this study also explores the challenges faced in practical applications, such as data quality, system integration, and technical costs, and proposes corresponding solutions. Finally, this paper looks forward to the development trend of artificial intelligence in future supply chain logistics management, and believes that with the further maturity of technology, artificial intelligence will play an increasingly important role in various links of the supply chain.

Shubing Chen. Research on Supply Chain Logistics Prediction and Decision Optimization Driven by Artificial Intelligence. Academic Journal of Business & Management (2025), Vol. 7, Issue 2: 132-139. https://doi.org/10.25236/AJBM.2025.070218.

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