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Introduction to AI in Supply Chain Management
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Author(s): Bartholomeus Dimanche Carl Beth (Universitas Esa Unggul, Indonesia), Ryan Putra Laksana (Universitas Esa Unggul, Indonesia), Binastya Anggara Sekti (Universitas Esa Unggul, Indonesia), Jefry Sunupurwa Asri (Universitas Esa Unggul, Indonesia)and Sawali Wahyu (Universitas Esa Unggul, Indonesia)
Copyright: 2027
Pages: 23
Source title:
Encyclopedia of Modern Artificial Intelligence
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Founding Editor-in-Chief, Information Resources Management Journal (IRMJ), USA)
DOI: 10.4018/406745
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Abstract
The application of AI in supply chain management brings significant changes to various critical functions, from demand forecasting to security and risk mitigation. In this article, each aspect will be discussed based on empirical evidence and the latest technology. AI technology enables companies to analyze large amounts of data in real time, detect demand patterns, optimize inventory, and make automated decisions that previously required lengthy manual processes. Additionally, AI can manage the complexity of highly dynamic global supply chains by enhancing visibility, resilience, and operational efficiency. Through the integration of machine learning, deep learning, and reinforcement learning, AI can adaptively adjust procurement strategies, logistics scheduling, and supplier evaluations. Even in terms of security and risk prevention, AI can proactively predict disruptions, analyze supply chain vulnerabilities, and detect anomalies and potential fraud. Therefore, AI is not just a tool but a strategic key to achieving a resilient, adaptive, and competitive supply chain.
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