The cargo industry is splitting into two camps. One believes automation replaces humans. The other believes automation removes routine work so humans can focus on operational complexity. Both paths make humans more valuable, not less.
Knowledge-retention crisis
While humans are increasingly moving upward in the operational stack, a huge amount of cargo operations currently depends on aging supervisors, undocumented workarounds, and informal relationships. As automation increases and senior people retire, tacit operational knowledge may disappear faster than expected.
A senior warehouse supervisor may know from experience that two simultaneous truck arrivals at a specific dock configuration will block forklift circulation for 20 minutes during peak export build-up. That operational instinct rarely exists inside software logic, yet it directly affects throughput, cut-off compliance, and aircraft loading reliability. How operators improvise under pressure remains deeply human.
Leadership detached from physical reality is the biggest future risk. If decision-makers only see dashboards, they will lose intuition, trust bad data, misunderstand constraints, and optimize unrealistic workflows.
Entry paths and training
AI should become a training amplifier, not only a labour replacement. Removing junior roles is not the answer. Those roles should evolve toward exception coordination, judgment environments, customer interaction, and recovery strategy.
The best future operators will understand both cargo operations and digital systems. Most companies are not thinking this way yet.
The Economics of Fragmentation
A pharma shipment arriving late from a trucking feeder into Frankfurt misses cargo build-up by 18 minutes. The ULD has already closed. The airline refuses late acceptance. The GHA manually rebuilds another pallet position while customs documents are revalidated. The forwarder escalates to secure uplift on the next flight. Two temperature-controlled shipments sit exposed on the ramp longer than planned while four organizations exchange calls, spreadsheets, and WhatsApp messages to recover the shipment. Nobody owns the recovery process end-to-end.
This is where air cargo still leaks money: not inside the aircraft itself, but at the interfaces between organizations. The industry still runs on fragmented systems, manual coordination, duplicated data entry, and reactive operations.
In a 2025 report, McKinsey Global Institute argues that the largest productivity gains from AI and automation come not from automating isolated tasks, but from redesigning entire operational workflows. In air cargo, that challenge becomes exponentially harder because disruption recovery spans multiple organizations with fragmented incentives and systems.
Why Ground Handling Agents (GHAs) matter
GHAs sit at the intersection. That makes them the most exposed, but also potentially the most strategically important. The industry often still underestimates them commercially.
Airlines externalize operational complexity while GHAs absorb execution risk. This increasingly compresses margins. Exception handling remains mostly unpaid: tracing freight, fixing paperwork, handling no-shows, rebuilding pallets, coordinating late cargo, dealing with truckers, and handling customs are often outside standard handling economics. In practice, many GHAs already coordinate operations, but they are still priced like warehouse labour.
GHAs sit on operational data they barely use, while airlines and forwarders would pay for operational predictability if the data were reliable. The risk for GHAs is that they continue creating process visibility while airlines, software vendors, and digital platforms capture the economic value.
Different strategic positions
No GHA has fully solved the industry’s core issues yet: cross-company coordination across fragmented cargo systems with misaligned incentives. Swissport continues emphasizing operational standardization at scale, while dnata benefits from its integration within The Emirates Group, allowing it to operate closer to an integrator model than many traditional GHAs.
Yet despite these different approaches, the industry’s core challenge remains largely unresolved: coordinating disruption recovery across fragmented systems, organizations, and incentives.Top of FormBottom of Form
The real battle
The industry is not moving toward “humanless cargo.” It is moving toward fewer humans with higher operational leverage.
The real battle is not who has the best AI. It is who controls recovery and decision-making across fragmented cargo systems.
