Agentic AI in Logistics: Why 55% Accuracy Fails

Agentic AI in logistics still breaks when spatial reasoning enters the picture. HERE Technologies’ Bart Coppelmans explains why general AI models can understand language but still fail on truck routing, low-clearance bridges, parking, congestion and real-world execution. In this FreightWaves Today segment, Bart lays out why location intelligence has to be built into logistics AI from the start—not bolted on later—and how better spatial grounding can connect planning, execution and driver feedback in real time. #LogisticsAI #SupplyChainTech #TruckingTechnology General-purpose large language models correctly answer only about 55% of basic direction questions, and that accuracy gap is directly blocking the adoption of agentic AI in logistics, according to Bart Coppelmans, head of enterprise product at HERE Technologies. The company, which has powered transport management, fleet management, and last-mile delivery systems for multiple decades, argues that location intelligence must be embedded at the foundation of any AI-driven logistics workflow — not added later.