As global cargo volumes continue to rise, logistics operators face increasing pressure to enhance operational efficiency while managing workforce constraints. The International Air Transport Association (IATA) notes a steady growth in air cargo demand, driven by e-commerce and global trade recovery. However, workforce availability in logistics and cargo handling has not kept pace. Many terminals still depend on manual workforce allocation and static shift planning, leading to

Understand why an AI-powered sustainability optimisation engine can be a critical component to scale sustainable air cargo operations.

Global logistics networks are operating in an environment where demand volatility has become structural rather than seasonal. Fluctuating trade flows, e-commerce acceleration, geopolitical disruptions, and changing consumer behaviour are creating unpredictable cargo movement patterns across ports, terminals, and distribution hubs. Yet many logistics operations still depend on historical averages and static planning models to manage infrastructure and resources. The result is