A while ago, I worked on a project for a North America-based logistics and freight operations company handling over 18,000 shipments every month across Chicago, Dallas, Toronto, and Los Angeles. At first, the project sounded relatively straightforward. Build smarter operational automation. Reduce manual coordination. Improve shipment visibility. Handle freight exceptions faster. Pretty standard enterprise AI discussion. But once we started mapping how the operations teams actually worked day to day, the problem became much more interesting. Because the real bottleneck wasn’t transportation. It was coordination. And coordination problems become surprisingly complex once multiple teams, systems, and operational priorities start colliding at scale. Fragmented Operations Dispatch teams worked separately from warehouse operations. Carrier communication happened across emails and spreadsheets. Customer support teams often received delayed shipment updates.…