AI in logistics: digital twins, everyday automation, and the risks that arrive beside them
Statista Research Department's overview of AI in logistics, dated December 17, 2025, describes digital twin technology, citing insights provided by Maersk, as a virtual replica of a physical asset such as a truck or a warehouse that lets a logistics operator identify issues along the supply chain in real time and react sooner. It places the everyday uses of AI in forecasting, inventory taking, route planning and the running of robots and forklifts, puts the worldwide cargo drone market at 17.88 billion U.S. dollars by 2030, and sets the risks beside the gains: the FBI recorded almost 300,000 phishing cases in the United States in 2023, criminals have used tools such as WormGPT to obtain customer information, and in a 2022 US survey of 1,059 people 43 percent were dissatisfied with AI customer service against 25 percent satisfied.
- $17.88bn Worldwide Cargo Drone Market By 2030, As Stated In The Statista Overview
- Almost 300,000 US Phishing Cases The FBI Recorded In 2023
- 43% Dissatisfied With AI Customer Service, 2022 US Survey Of 1,059 People
A digital twin earns its keep on the exceptions. The value the overview describes is seeing a problem in a truck or a warehouse in real time and reacting sooner, which for a buyer is a visibility and exception management purchase rather than a new system, and the strongest supplier case is the twin as a layer on data the operation already collects. The everyday uses are unglamorous and already in place, forecasting, inventory taking, route planning and running robots and forklifts, so an AI pitch to the buyers on the program competes on those lines, not on novelty. The risks sit beside the gains and both reach the last mile: phishing volumes and AI assisted data theft land on parcel and 3PL networks, and the 2022 survey the overview cites found more respondents dissatisfied than satisfied with AI service assistants, so identity, fraud and customer communication suppliers have a case that belongs next to the automation case. And the Rwanda blood delivery example is a reminder that drone delivery is already commercial where the ground network cannot reach, not a forecast.