The machine will work when the refrigerated or frozen product shipment arrives at the system's logistics warehouse. Computer Vision Technology scans palettes and log data about customers, product types, and item descriptions. AI-driven algorithms combine shipping data with historical information to predict when a truck will remove goods from the warehouse. The technology assigns warehouse spots to pallets based on how long they stay at the facility and tells the forklift operator where to go.
This level of technology can improve the efficiency of all types of supply chains, but it is important in cold warehouses where products such as frozen foods, fresh produce, and pharmaceuticals are stored. A short deviation in temperature can damage the cargo, and warehouse managers do not want workers to spend time without breaks under zero conditions. This makes accuracy and productivity essential in cold chains.
Refrigerated and temperature sensor technology has been essential for cold chains for decades, but now advanced versions are permeating the industry. Cold chain providers have abandoned the manual processes of AI-driven algorithms and explored digital twins and AI agents to make highly automated operations even more autonomous.
“Whether it's 50 years old technology or cutting-edge AI, technology is very widespread in the cold chain,” Sudarsan Thattai, Chief Information Officer and Chief Transformation Officer at Lineage Logistics, told Business Insider.
Cold Chain warms up to predictive AI
One way that strains use AI is using decision-making algorithms. Once poultry delivery from a strained customer arrives at the warehouse, the algorithm determines where the product will be placed to minimize walking or driving distance in the warehouse.
The entire turkey will not be in store until November, but the meat from the deli is transported and sold all year round. This algorithm tells the forklift operator to place the entire turkey on a high shelf behind the warehouse, while the sliced turkey can be placed near the front for sandwiches.
“It cuts down the miles I need to drive to help me choose that pallet and clean it up,” said the tie. “Because I don't want to fill up the meat in the deli, I'm going to dig into the extra energy for now.”
Company president Rob Chambers said Americad, a cold chain provider, “has a strong interest in innovation across all cold chain sectors.” Pharmaceuticals, fresh produce and specialized foods often lead the way in technology adoption due to regulations and temperature sensitivity that require highly controlled and actively monitored supply chains.
According to Chambers, customers aren't necessarily looking for AI by name from Americold, but they are expected to have fewer “outcomes that AI can offer,” less stock, and the ability to respond quickly to changes in real time. Cold chain companies are investing in predictive analytics to better understand customer demand and how food flows through the supply chain. That way, Americad can actively plan warehouse capacity, Chambers said.
Unilever, who owns ice cream brands such as Magnum and Ben & Jerry's, also uses AI to use it for prediction. The consumer goods company operates a cold chain spanning 35 production lines and 3 million ice cream freezer cabinets in 60 countries. Unilever's supply chain team uses AI to analyze weather inputs. This allows you to predict how many ice cream consumers will be able to purchase in a particular area. If a heat wave comes, the demand for ice cream can increase, and AI-based inventory systems can propose decisions on how to allocate inventory. According to a January report from Unilever, the AI tool has improved prediction accuracy by 10% in Sweden. In the US, sales increased by 12%.
Forecasting not only guides inventory strategies, but also helps managers decide how many trucks they need and the best way to get in and out of warehouses, says Ron Leibman, Chair of Transport, Logistics and Supply Chain Management Practices at McCarter & English.
“A lot of this has been going on for a long time. It's just that AI is different, faster and perhaps better,” Liveman said.
Cold Chain Data Sharing Black Hole
Americand and Lineage consider the possibility that AI will expand in the cold chain.
Americand is exploring digital twins that create virtual replicas of warehouses used for simulation and planning. We are also considering AI-guided robots that select products in cold environments.
With temperature monitoring, the technology has already gone beyond recording temperatures to sending an alert when the temperature goes out of range, Thattai said. Large language models can be trained on temperature excursions, making it easier and inexpensive to deploy AI to detect changes.
ThiTAI foresees that AI agents will automatically adjust warehouse reservation times based on real-time location data on tracks, rather than using quotes or phones. The Thailand jokes that if they call a truck driver and ask for their location, they say they're 10 minutes away no matter what.
However, one shortage is visibility and data sharing across the cold chain. The Thailand said it has progressed, but it is not ubiquitous.
“Data sharing is one of the big areas that are black holes,” he said.
Not all companies share real-time data, Thattai said. Independent or small truck fleets may not use as much technology as large truck carriers. The producers are “not very sophisticated,” Liveman said. They often use manual documents that list the types and amounts of fruits and vegetables to pick.
These types of manual processes do not help with data sharing in cold chains. Without data, AI does not have the basis for making predictions.
“We're not at the point where we're making the most of artificial intelligence,” Liveman said.
