Warehouse operators are investing in AI to improve planning, inventory control and fulfilment. But the technology’s commercial value depends on whether its view of the operation is accurate. A system that says stock is available in a location does not help if the item is elsewhere or the space is already occupied.
Oana Jinga, Chief Commercial and Product Officer at Dexory, discussed the issue with Peter MacLeod. She highlighted the gap that can develop between a Warehouse Management System and the physical warehouse. That gap can undermine picking productivity, order completeness and customer service.
Inventory accuracy is only one requirement. AI also needs information about rack layouts, warehouse space, movement, machinery and the dimensions of goods. This broader combination of digital and physical information is helping shape Physical AI for logistics.
The financial impact of errors can be disproportionate to their apparent size. Staff may spend time locating stock or investigating discrepancies, while incomplete orders and production interruptions add further cost. Maintaining accurate data therefore affects more than inventory KPIs; it can influence productivity, service levels and profitability.
Robotics and connected data may enable increasingly sophisticated operational decisions, but the judgement of experienced warehouse managers remains relevant. Companies should first define the process problem, assess the quality of their existing information and then select technology that addresses it. For warehouse AI, reliable facts on the floor are a business requirement, not an optional extra.
A multilingual professional experienced in Europe, Canada, and China, Herbert has developed invaluable networks in the automotive and energy industries. He has led high-profile projects involving ENBW, Mercedes-Benz Group, Siemens Group, and the Fraunhofer Institute.