AI in Warehouse Logistics

Store associates are the face of retail organizations. To maximize time with customers, retailers are working to reduce the time they spend on non-customer-facing tasks, such as inventory counts. Large retailers are using robotics technology to unload and sort items based on priority and department, check stock levels, correct shelf locations, and ensure price accuracy.

To resolve throughput challenges from the scale and variety of products, companies are using edge computing to detect, classify, estimate the size of, and position packages, automatically adjust the speed of conveyors and optimize mechanical sorting. This helps to minimize product damage and machine downtime.

Several factors can impact the last mile of delivery, including traffic, construction, and weather. Using real-time data from a variety of sources—from GPS data to weather forecasts—routes can be optimized, which can significantly impact fuel, personnel, and other overhead costs. Beyond that, by using GPU-powered smart solutions to optimize routes, carriers can provide more accurate delivery windows, improving the level of service provided to customers. This instills a higher degree of trust, which matters when customers have an array of options for sending and receiving important parcels.