An AI platform that integrates freight forwarders, airlines, ground handling agents, and trucking companies is now being implemented in major global cargo hubs. According to Ground Handling International, Miami International Airport launched its Airport Cargo Community System (ACCS) on October 29, 2026. The platform was developed by Kalé Logistics, a logistics technology company headquartered in Mumbai. Industry media outlet Airport AI Alliance reported on November 1 that the airport expects the platform to generate annual savings of up to $250 million for its cargo supply chain. Let's put that figure out there for now, but whether it can actually be realized remains to be seen.
Miami Airport boasts a substantial cargo operation. According to data cited by Airport AI Alliance, it handled 3.4 million metric tons of cargo in 2025, setting a new record. The airport has long been a major U.S. gateway for cargo, with flowers, fruits, and seafood being common commodities. The problem lies in the way operations are coordinated. Freight forwarders, airlines, ground handlers, and trucking companies each operate independently, with fragmented communication and many processes relying on manual intervention, which naturally limits efficiency. The new platform aims to replace this fragmented system by connecting all stakeholders on a shared digital platform. According to Payload Asia, the project's goals include alleviating truck congestion, accelerating cargo handling, improving resource planning, and reducing carbon emissions.
The airport authorities, however, have not committed to a definitive timeline. Ralph Cutié, President and CEO, told the Airport AI Alliance that the project is still in its early stages, and further communication with the cargo community, as well as the onboarding and training of new users, are required before the platform can be deployed. He also stated that the outcome of these steps will determine the advice the airport gives to other airports.
In an email statement to the media, Amar More, co-founder and CEO of Kalé, explained that the platform is designed with an “AI-first, API-first” approach and incorporates several automation tools. The document processing agent combines OCR with AI to extract information from PDF files and convert it into structured system data, reducing the time drivers spend at the freight station counter. Predictive tools estimate truck turnaround times, allowing transportation companies to anticipate potential delays. The dispatch optimization agent is responsible for assigning vehicles to loading and unloading bays, minimizing queuing and waiting times. Additionally, there is a multilingual generative AI chatbot that answers inquiries about cargo status, outstanding payments, customs clearance progress, and estimated time of arrival, replacing some phone calls and email correspondence.
There are two more features to be added. The freight volume forecasting function is used for resource planning, and the anomaly detection feature will be launched in a later phase.
How did the figure of $250 million come about? Mohr explained that it represents the total savings across the entire cargo supply chain, not just at the airport. The savings come from various sources, including reduced document processing time, labor costs for follow-up communication, fuel savings due to shorter truck waiting times, reduced overtime pay for drivers, decreased costs associated with paper-based documentation, and fewer penalties. He emphasized that these benefits are currently projected and depend on the level of adoption within the cargo community. The actual results will only be visible once the system is fully implemented and used by the community, which is expected to take about one to one and a half years.
Previously, AI applications in air cargo have primarily focused on individual processes, such as warehouse sorting or load forecasting. Integrating all aspects of an airport's cargo operations onto a single platform is a relatively new approach. According to the airport, this is the first attempt by a global cargo airport to introduce such an AI platform, and potential questions from industry peers have been addressed in advance through public reports. Once the initial operational data is available, the cost-benefit ratio of the cargo community system will provide a benchmark, allowing other airports interested in implementing similar systems to directly compare their results.