Air cargo is an industry that is constantly on the move and one that is governed by volatility, urgency, and strict time schedules. On any given day, shipments are booked or rebooked, available capacity shifts, customers request status updates, documents need checking, load plans are created taking care to ensure co-loadability of commodities and efficient space utilisation, and across the world, logistics teams are working to mould a multitude of requirements into reliable transport promises.

People in air cargo are thus permanently under pressure to solve challenges and deliver. This is an industry that stands to benefit exponentially from the ever-increasing number of AI solutions, while at the same time maintaining its human character. Air cargo is very much a people business and AI has the potential to make it even more so.

Translating AI potential into everyday operational value

There is almost no limit to the number of workflows that lend themselves to AI enhancement. However, the industry’s most immediate opportunity is in removing some of the pressure from frontline operations. The tangible gains for businesses therefore lie in embedding AI into day-to-day workflows.

Frontline teams manage a constant stream of time-critical requests: quotations, booking confirmations, track-and-trace enquiries, schedule changes and shipment modifications. For years, much of this work has depended on inboxes, manual follow-up, and individual experience. Digital platforms such as CargoTech’s CargoAi are changing that rhythm by bringing eQuote, eBooking and track-and-trace capabilities into a more connected operating environment. The result is not simply faster administration. It is a redefinition of the employee’s role, from processor of transactions to orchestrator of outcomes.

AI as a force multiplier, not a human replacement

And that forms the foundation for the next level in AI adoption: Agentic AI. The most effective AI workplaces will be those that go beyond basic automation and combine machine speed with human judgement. Agentic AI can already support multi-step, semi-autonomous tasks – from interpreting a customer request and checking capacity, to comparing options or retrieving a shipment status, for example. CargoAi’s CargoMart platform, where AI agents work alongside human agents, illustrates an existing balanced model. And this technology is continuously maturing. AI absorbs repetition and scale, and learns from historical data; people bring accountability, negotiation, commercial sensitivity and contextual intelligence into the equation. The workplace becomes more automated, but also more deliberately human – a model that reflects CargoTech’s philosophy that AI augments rather than replaces human expertise.

Elevating customer care through proactive, AI-driven engagement

Customer care is where this AI/human balance becomes most tangible. Air cargo customers want information fast, and they want confidence. CargoTech’s member companies offer integrated platforms that empower customer-facing teams to move from reactive updates to anticipatory engagement, using live visibility, scenario planning and actionable intelligence to predict or identify any possible disruption sooner and before the customer reports an issue.

In the event of Aircraft on Ground situations, shipment offloads, missed connections or capacity disruption, AI can quickly establish any affected shipments and suggest recovery options. It enables the simultaneous management and communication of those critical events across multiple customer touchpoints. Based on real-time information, human teams then make the decisions that matter most: what to prioritize, how to communicate and how to preserve customer trust when operations do not go to plan.

Reimagining performance management through AI-driven analytics

A similar AI shift is emerging in performance management. Traditionally, analysing operational performance has required labour-intensive coding, formula building, and manual reporting. AI-driven analytics change the conversation. Instead of asking who has the technical expertise to produce a specific report, air cargo teams can use natural language prompts to request AI to analyse complex datasets and model diverse customer scenarios which then aid human decision-making. Wiremind Cargo’s CargoStack suite, using machine learning models trained on customer data, demonstrates how complex datasets can be interrogated at greater speed and scale. Rotate’s consultant-led approach adds a crucial layer: digital transition is not only about tools, but about industry knowledge, change management and selecting the right problems to solve and performance metrics to measure.

A people story, powered by technology

AI enhancement and adoption is ultimately a people story. It will change roles, but not by making human expertise obsolete. If implemented well, it will give teams more room to solve problems, manage customer relationships and improve service. It will push managers to rethink workflows, rather than simply digitise existing ones. AI’s success will be shaped by the choices they make: which processes to redesign, which decisions to accelerate, which risks to control, and which human strengths to protect.

AI can reduce friction, improve responsiveness, support better customer engagement and make insight available to more people. Humans bring context, accountability and trust. Put together, they offer something more powerful than either could deliver alone: an air cargo industry that is faster, more resilient and still unmistakably human.