What is an example of an AI application in supply chain management?

Demand forecasting through predictive analytics is an exemplary application of artificial intelligence in supply chain management. This approach utilizes historical sales data, market trends, and other relevant information to predict future customer demand accurately. By leveraging machine learning algorithms, businesses can identify patterns and adjust their inventory levels accordingly, reducing the risk of stockouts or overstock situations.

Effective demand forecasting enhances decision-making processes in supply chain management by enabling companies to allocate resources more efficiently, plan production runs more accurately, and optimize inventory levels. This not only improves customer satisfaction by ensuring product availability but also enhances overall operational efficiency and cost-effectiveness.

Although the other options provide valuable functions within supply chain management, they are not as directly focused on the predictive aspect of demand, which plays a crucial role in planning and strategy. Automated inventory checks and customer service automation help streamline processes, while logistics route planning enhances transportation efficiency, but they do not specifically address forecasting demand based on predictive analytics.