Quotation and booking management remain surprisingly resource-intensive across airline cargo sales, and slow quote responses still cost carriers missed commercial opportunities — despite years of investment in digital platforms. That is the assessment of Cédric Millet, President of CargoTech, who argues the industry's technology problem is fundamentally a business transformation challenge, not an IT one.

"Too many businesses treat digitalisation as an IT problem to solve, when it's really a business transformation driven by clear objectives," Millet told Air Cargo Week.

The distinction matters. Air cargo companies have spent years deploying new platforms, automated processes and connected systems, yet adding technology without wider organisational change often makes operations more complex, not less. In Millet's view, successful implementations share one trait: leadership drives them.

"In every successful implementation we've seen, leadership and the business itself have driven the change, not IT alone. A forward-looking culture is what makes new technology stick. The moment you introduce new tools without changing anything else around them, you've simply added complexity, not removed it," he said.

Resistance is rarely technical in origin. Employees are familiar with established processes even when those processes are inefficient or labour-intensive, and Millet argues that humans' habitual nature means new tools require strong change management to achieve real adoption.

Where the revenue leaks

The business-led gap is most visible in airline cargo sales and revenue management. Millet points to two areas of significant exposure.

First, quotation and booking management still consume substantial resources, while delays in responding to customers directly affect commercial opportunities. Conversion rates, he notes, are hard to track with any real precision.

Second, and larger: capacity management. "The biggest revenue loss sits with the gap in capacity management capabilities (which Wiremind Cargo developed), namely capacity forecasting and overbooking," Millet said.

Airlines also make daily decisions on allocations, free-sale capacity, entry conditions, product mix and origin-and-destination pairings. Too much of that decision-making rests on individual experience and judgement, which consumes time and creates dependency on a handful of key people, according to Millet.

Manual processes persist in shipment approval as well, with airlines still queueing requests and approving bookings by hand to protect revenue.

For transit carriers, the problems extend beyond the initial booking. Delays and schedule changes force planners to rebalance cargo across the network, raising the risk of missed connections and offloaded freight. Millet described central planning teams and station ground handling agents as caught in "an endless loop to repair shipments".

A fragmented chain

Individual carriers and forwarders have made real progress transforming their own organisations, but the wider cargo journey still involves airlines, forwarders and ground handlers with different systems, investment levels and technological capabilities. The next challenge, Millet said, is tackling the value chain as a whole.

Fragmentation makes consistent data exchange difficult, particularly when country-specific regulatory requirements enter the process. "Without standardised frameworks, automation and digitalisation become far harder to execute well," he said.

CargoTech's response has been to invest in software companies built with an API-native structure, aiming to reduce the integration burden on customers adopting new cargo technologies. "Because our companies are API-native, connectivity is seamless when it's built in from the start rather than bolted on later," Millet explained.

He also expects software requirements to shift as AI embeds itself in cargo operations. "As we move deeper into the AI era, MCP-ready software is quickly becoming a baseline requirement, not a nice-to-have."

Co-pilot, not replacement

CargoTech does not see every cargo process as a candidate for full automation. Millet draws a line between repetitive transactional work and strategic decisions such as network planning and revenue optimisation. "What you can do is equip users with solutions that act as CoPilots so that they can make the best-informed decisions," he said.

AI can create measurable value by operating continuously, processing large data volumes and executing high numbers of transactions simultaneously, with repetitive transactional activity the most immediate opportunity. The next stage would see AI learn buying requirements and proactively search for suitable offers, cutting the multiple calls and website searches employees currently perform.

The wider transformation, however, will still depend on people — and on leadership that treats digitalisation as a commercial discipline rather than a technology rollout.