United States Cold Storage (USCS) has implemented an artificial intelligence agent to automate its appointment scheduling process, a move aimed at improving operational efficiency across its national network. The company adopted the AI agent, named Alan, from the supply chain visibility provider FourKites, following a successful pilot program that demonstrated significant reductions in manual labor and high accuracy rates.
Key Takeaways
- United States Cold Storage is using FourKites' AI agent, Alan, to automate appointment scheduling for inbound and outbound logistics.
- An eight-week pilot program showed an 87% success rate in autonomously booking appointments and a 96% accuracy rate in securing requested dates.
- The automation saved an estimated 36 to 40 hours of manual work during the test period by handling over 600 shipments.
- The AI agent can process more than 150 scheduling requests at the same time, operating 24/7 without human intervention.
Addressing a Major Logistics Bottleneck
United States Cold Storage, a major operator of temperature-controlled warehouses with 38 facilities across the country, identified appointment scheduling as a primary source of inefficiency. The process of coordinating deliveries and dispatches in a highly regulated environment has traditionally been a labor-intensive task.
Logistics teams often spend hours managing a constant flow of emails, phone calls, and various web portal logins to secure time slots for shipments. This manual back-and-forth created delays and consumed valuable staff resources that could be allocated to more critical operational duties.
The Complexity of Cold Chain Logistics
The cold storage industry requires precise timing and coordination to maintain the integrity of temperature-sensitive goods like food and pharmaceuticals. Delays in scheduling can lead to product spoilage, regulatory compliance issues, and significant financial losses. Efficiently managing inbound and outbound traffic is therefore critical to business operations.
Recognizing the potential for automation to streamline this process, USCS partnered with FourKites, a company it already used for shipment tracking and visibility services. The goal was to test whether an AI agent could handle the complex and repetitive task of scheduling appointments without human oversight.
Pilot Program Delivers Strong Results
To validate the technology, USCS and FourKites conducted an eight-week pilot program. During this period, the AI agent Alan was tasked with managing real-world scheduling requests for over 600 shipments.
The results of the trial were significant. The AI agent successfully booked appointments with an 87% success rate. Furthermore, it achieved 96% accuracy in securing the delivery dates specifically requested by customers, demonstrating its ability to meet precise logistical requirements.
Productivity Impact
The pilot program resulted in a productivity increase equivalent to saving between 36 and 40 hours of human work. Alan operated around the clock and could handle more than 150 scheduling requests simultaneously, a stark contrast to the one-at-a-time pace of a human coordinator.
The system was well-received by those who interacted with it. According to Keith Mowery, Executive Vice President for Logistics & West Region at United States Cold Storage, the initial reaction was one of surprise and enthusiasm.
“The first individuals who interacted with the agent were actually amazed and very intrigued by this product and the idea of a digital agent and how—through utilizing technology—an appointment was just made with no human interaction,” Mowery stated. “The group was very excited by how easy it was to use.”
How the AI Technology Works
The AI agent Alan operates differently from traditional robotic process automation (RPA). While RPA systems typically follow rigid, pre-programmed scripts, Alan uses a more advanced, context-aware intelligence. This allows it to adapt to different communication methods and interfaces without needing custom code for every variation.
The system can interact with emails, web portals, and even phone systems in real time. It understands the context of a request, navigates different scheduling platforms, and completes the booking process autonomously while maintaining a clear audit trail for human supervisors to review.
Integration with Broader Supply Chain Data
A key feature of Alan is its integration within FourKites' Intelligent Control Tower platform. This platform already processes more than 3.2 million supply chain events daily, giving the AI agent access to a vast network of real-time data.
This broader awareness of supply chain conditions, such as traffic delays or warehouse congestion, allows the AI to make more informed scheduling decisions than a standalone automation tool could. It can anticipate potential disruptions and adjust schedules accordingly, a capability that moves beyond simple task automation.
Implications for the Logistics Industry
The successful implementation at USCS highlights a potential shift in how logistics companies manage administrative tasks. Manual appointment scheduling has long been a choke point across the industry, consuming resources and creating operational friction.
The use of AI agents grounded in real-time data offers a scalable solution to this problem. For USCS, the benefits extend beyond just efficiency gains. By creating smoother operations and freeing up staff, the company can enhance its customer service and gain a competitive edge in the market.
For FourKites, this case study reinforces its strategy of positioning AI not merely as a background tool but as an active partner in supply chain execution. The success at USCS serves as a model for how other companies in transportation and logistics can leverage autonomous technology to solve persistent operational challenges and reduce costs.