IN Brief:
- Wiliot and AT&T Business are expanding collaboration on enterprise Physical AI deployments.
- The partnership combines item-level sensing, gateway certification, connectivity, field execution, and systems integration.
- Deployments are already underway across retail, food and beverage, logistics, and parcel environments.
Wiliot and AT&T Business are expanding collaboration on Physical AI deployments across enterprise supply chains, targeting item-level visibility in retail, food and beverage, logistics, post and parcel, and quick-service restaurant environments.
The collaboration combines Wiliot’s ambient IoT and sensing platform with AT&T’s network infrastructure, cellular connectivity, device certification, systems integration, installation support, asset tagging, and field execution. The model is designed for complex supply chains where visibility depends on millions of tagged assets, products, cases, or handling units.
Wiliot’s platform uses battery-free IoT Pixels to capture data from physical assets and feed that information into digital systems. AT&T’s role includes gateway certification on its network, site design, installation, maintenance, and field operations, helping move deployments beyond proof-of-concept environments.
The companies are positioning the work around Physical AI, where live data from products and assets can be used to support automated decisions across inventory, receiving, shipping, replenishment, and exception management. Reported deployment outcomes include inventory accuracy above 99%, dock-to-stock time reduced from 24–48 hours to 2–6 hours, receiving labour reductions of 30–50%, mis-shipments cut by up to 90%, and lost, damaged, or delayed packages reduced by 60%.
The technology sits across several pressure points in modern logistics. Inventory visibility has become more valuable after years of disruption, overstocking, shortages, and service volatility, while labour pressure is pushing operators to reduce manual scanning, reconciliation, and exception handling.
Item-level sensing is particularly useful in food, retail, and parcel logistics, where products move quickly and poor data quality can create waste, missed service windows, or unnecessary handling. In temperature-sensitive and time-sensitive supply chains, more accurate signals can support better decisions around dwell time, stock rotation, prioritisation, and product condition.
The same pressure is shaping warehouse operations. Romark’s deployment of DexoryView for real-time inventory visibility reflects the move away from periodic checks and towards continuous operational data. Wiliot and AT&T are approaching the same problem through sensing and connectivity, with physical goods feeding live data into operating systems.
AT&T’s role highlights a practical barrier that often slows supply chain technology adoption. Large visibility projects can fail to scale when installation is too complex, connectivity is unreliable, field support is weak, or integration depends on excessive site-by-site customisation. Enterprise operators need deployment partners that can support thousands of locations, not only one successful trial.
Connectivity is central to that challenge. Warehouses, stores, vehicles, depots, and parcel facilities are not uniform environments. Assets may move through areas with different network quality, layouts, temperature conditions, and handling processes. Reliable data capture requires the physical infrastructure and digital platform to be designed together.
Physical AI also depends on trust in data quality. Automated decision-making is only useful when the system can rely on what it sees. Incomplete, delayed, or inconsistent sensing data pushes teams back towards manual checks, undermining the value of automation.
As supply chains become more automated, item-level visibility is likely to become part of the operating layer rather than a reporting enhancement. Warehouse systems, transport platforms, and planning tools all depend on accurate input from the physical world. Wiliot and AT&T are aiming at that interface, where products, assets, and digital workflows meet.
