Abstract
Artificial intelligence and machine learning are being implemented by a constantly growing number of companies to develop a more efficient supply chain. The immense volume of data that companies are producing and sourcing along the supply chain can now be analyzed in real time, enabling better decision-making processes. This paper will explore how the utilization of these technologies is revolutionizing supply chain management. Two specific areas, demand forecasting, and inventory management, will be explored in greater depth. The paper will then highlight the current trends and challenges of AI and ML in supply chain management and offer concluding remarks.
Supply chain management is a complex system that connects multiple companies and encompasses the flow of goods, services, information, and finances. To cope with its complexity, more and more companies are turning to technologies like artificial intelligence (AI) and machine learning (ML) to gain a competitive edge. ML is a branch of AI that consists of systems and algorithms that can learn from data to improve decision-making. The number of companies that claim to be using ML has grown by more than 300% since 2015, with the overall AI market considered to be worth around $2 trillion. In the supply chain industry, companies are using ML to optimize delivery routes and times, predict delays and detect variances in quality at an early stage. The use of AI technologies can optimize and execute supply chain tasks promptly, making it more capable than traditional supply chain setups.
Keywords
References
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