AI routing systems fail on real-world logistics constraints, causing missed deliveries and inefficient routes

Logistics companies implementing AI-powered routing systems experience critical failures when spatial reasoning is required—trucks get routed under low-clearance bridges, into impossible parking situations, or through congested areas that generic AI models can't understand. Current agentic AI solutions achieve only 55% accuracy on real-world execution, forcing logistics operators to manually override routes and lose the efficiency gains they paid for, while competitors using location-intelligent systems outperform them.