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Traditional demand planning methods often struggle to keep pace with the complexity, volatility, and vast datasets inherent in modern supply chains. Artificial intelligence (AI) offers a transformative solution, revolutionizing demand planning with its ability to analyze vast amount of data, identify complex patterns, and generate highly accurate forecasts. This paper explores the latest advancements in AI for demand planning, encompassing machine learning, deep learning, and natural language processing (NLP). The focus is on how these techniques enhance demand sensing capabilities, incorporating real-time market signals, external data sources, and unstructured text information. Furthermore, the potential of AI to optimize inventory management, enable scenario planning, and increase supply chain resilience in response to unexpected disruptions are examined. The paper also addresses practical challenges in implementing AI-powered demand planning solutions, and outlines areas for future research. Most importantly, the paper provides the robust methologies to integrate the emerging AI developments in demand planning process.
Khastgir et al. (Mon,) studied this question.