Digital tools target air cargo delays and unused capacity

By Priya Raman

LATAM Cargo has delivered 45 digital products through a transformation programme involving about 18 teams, with five more planned for the fourth quarter. At TIACA’s Air Cargo Forum in Miami last month, chief executive Andrés Bianchi said the programme represented the company’s largest-ever investment outside freighter aircraft (dedicated freighters); he declined to disclose the amount.

The programme began with LATAM Cargo moving away from departmental silos and identifying where performance needed improvement. Bianchi described a different way of working: asking employees what they need to deliver using technology. LATAM first considers whether existing software meets its requirements, but he estimated 80% to 90% of what it needed was suitable for in-house development.

Customer priorities are reliability, speed and peace of mind. The products target shipments that missed flights because of documentation or communication failures, addressing causes rather than merely reproducing traditional airline information services. Tracking functions can also deliver shipment updates through channels other than a customer website.

Improved aircraft loading and planning could release capacity on constrained lanes. Bianchi cited finding an additional 5% payload (carrying capacity available for freight) as an example of the potential benefit, not a result already achieved. LATAM had not turned that example into a quantified achieved gain.

Atlas Air’s Network Decision Support Tool evaluates recovery options after aircraft and crew disruption. A weather delay can leave a crew unable to operate its next flight within permitted hours; replacing it raises questions over positioning, cost, and whether an aircraft reaches maintenance with sufficient time and staff. Atlas does not follow a conventional hub-and-spoke network, which complicates those choices.

The tool produces recommendations within milliseconds and assesses the cost and operational consequences of each recovery option. Drew said: “It’s such a complex sort of jigsaw.” The exercise had been largely manual and could produce less-effective decisions.

Atlas built the tools through a transformation team combining internal operational expertise with recruits from consultants and other airlines. The company also brought data together on a Databricks platform to support decision-making. Future development covers maintenance planning, aircraft routing, integrated aircraft-and-crew scheduling, and forecasting using larger data volumes; those modules remain planned work rather than established service.

At Changi Airport, early results from truck-dock slot booking cut waiting times for cargo lodgement by about 25%, according to Jaisey Yip, vice president of its cargo business division. Cargo lodgement means submitting documentation electronically to authorities or handlers before physical cargo arrives. Changi introduced the system in 2024 and extended it to collection the following year.

The booking system coordinates trucks with shipment readiness and warehouse resources, replacing uncoordinated arrivals with planned visits aligned to handlers’ available dock capacity. Changi works with SATS, dnata and technology partners. A 2027 enhanced version would integrate more deeply with handlers’ cargo-management systems and allow multiple slots to be consolidated into one trip.

Changi also trials Aircraft 360, which uses computer vision and AI to monitor milestones during aircraft turnarounds (ground servicing between flights). If a process falls behind, the system alerts operational partners so they can redeploy resources before delays spread. Yip reported early improvements in turnaround punctuality but provided no numerical result.

Autonomous cargo transport remains under test at Changi. SATS is trialling vehicles to move shipments between its import terminal and forwarders’ warehouses inside the airport free trade zone. Driverless baggage tractors already operate, but extending the technology to cargo towing requires further work.

What does this change for shippers?

Operating tools already target three failure points: documentation-related missed flights at LATAM Cargo, disrupted aircraft and crews at Atlas Air, and uncoordinated truck arrivals at Changi Airport. Atlas’s recommendations arrive within milliseconds, but no quantified cost saving or capacity gain accompanied the tool. Changi’s roughly 25% reduction in cargo-lodgement waiting time is the clearest measured gain, while its turnaround punctuality improvement remains unquantified.

LATAM Cargo’s 5% additional-payload example is potential rather than achieved capacity. Atlas’s planned scheduling modules, Changi’s 2027 integration and SATS’s cargo-towing work remain outside present service. That separation matters because pilots and early operational results provide a firmer basis for decisions than development targets.

LATAM Cargo’s technology strategy also depends on retaining staff who understand customer problems and can act on information. Bianchi said: “AI will help you make better decisions. The people at the front are going to make those decisions.”

Until completed product rollouts and network-level operating data are available, Changi’s 25% waiting-time reduction remains the strongest measured result across the three programmes. The next phase will test whether faster disruption recovery, deeper handler integration and additional in-house tools can convert early operational gains into measurable cost, capacity and reliability improvements.