Artificial Intelligence (AI) has significantly contributed to the growth of various sectors and industries. One of the most significant contributions of AI applications is in forecasting. Consumer demand fluctuates faster than ever as a result of economic growth, advances in technology, and higher customer expectations, making forecasting future demand more difficult. Demand forecasting is a vital operation of supply chain management that aids in the best matching of supply and demand. Thus, improving demand forecasting accuracy is critical for companies and supply chains. Thanks to AI, businesses can accurately predict customer behavior. The study aims to provide a comprehensive review of how AI has been applied to forecast demand over the last decade. This research collects articles published between 2013 and 2023. According to the findings, AI is increasingly being used for demand forecasting in recent years. Energy and water demand forecasts receive the most attention. Long Short-Term Memory has gained prominence because of its advantages. Besides, this study will highlight the challenges of the adoption of AI. One of these challenges is selecting different reliable and suitable forecasting inputs for each AI method. This review will help supply chain managers and analysts select and implement suitable forecasting methods. Furthermore, this study will suggest some future research directions.

@article{oscm-2023-58,
  title={Applications of Artificial Intelligence for Demand Forecasting},
  year={2023},
  author={Thi Thuy Hanh Nguyen},
  journal={Operations and Supply Chain Management: An International Journal},
  volume={16},
  number={4},
  pages={424--434},
  doi={10.31387/oscm0550401}
}

Thi Thuy Hanh Nguyen (2023). Applications of Artificial Intelligence for Demand Forecasting. Operations and Supply Chain Management: An International Journal, 16(4), 424-434. https://doi.org/10.31387/oscm0550401