AI APPLICATIONS IN SUPPLY CHAIN MANAGEMENT

Supply chain management (SCM) practices are being rapidly integrated with Artificial Intelligence (AI), augmented the effectiveness, quickness, and decision-making processes of businesses. This discussion aims to elaborate on the problems anchored on the prevalence of AI technologies in SCM functions that include demand forecasting, inventory management, logistics optimization, and supplier relationship management. This specific case of demand forecasting involve the use of Artificial Intelligence technology that can help in early identification of overstock or stock out points based on historical data, market trends as well as other factors which helps categorize products that have high likelihood of going out of stock. In the case of inventory control, AI helps to provide constant and prompt checks on the stock levels, hence the best strategies on stocking and the possible cuts on costs. AI has the positive impact on logistics optimization by helping to find the best routes and manage the fleets and equipment for delivering the goods faster and with less failure in maintenance plans. Moreover, AI expands the abilities to maintain suppliers’ relationships since it helps identify risks related to suppliers and develop effective measures to solve them in advance. However, issues including data integration challenges, algorithmic prejudices, and scarcity of skilled personnel in AI are still key factors affecting AI’s growth. The future trends include the application of AI combined with other advanced technologies such as blockchain and IoT with the aim of improving the reliability and authenticity of the supply chains. This abstract emphasizes on the positive impact of Artificial Intelligence in SCM and while pointing out the need for businesses to manage the complexities of AI implementation in getting better strategic value of SCM in the growing world of AI supported SCM.