AI in Logistics is applied everywhere decisions are made about time, route and quantity. The most widespread deployments include route planning and optimisation taking into account capacity, time windows and traffic, demand prediction, which reduces capital tied up in inventory as well as the risk of stockouts, warehouse management including placing goods according to turnover rate, and automatic processing of shipping documents, orders and invoices, which saves the most administrative time. Additionally, delay prediction and automatic customer communication about shipment status are used. The condition is order in the master data – inaccurate dimensions, weights and addresses will undermine any optimisation. Start with document processing, which is the least dependent on integrations and delivers results within weeks.
See also: AI use case, AI in Manufacturing, Grant for Company Digitalisation.
