• Air cargo generates massive amounts of data, but airlines struggle to prioritise actionable insights; overcomplicated dashboards and unfiltered reporting often create analysis paralysis rather than clarity.
• Effective use of AI and predictive tools requires human expertise—combining business knowledge with machine learning allows airlines to interpret trends, anticipate capacity needs, and respond to unexpected disruptions more effectively.
• Focused scenario planning and monitoring key metrics, such as demand by vertical, freighter deployment, and future order books, enable agile route planning, fleet allocation, and customer service, making flexibility more valuable than perfect forecasts.

Air cargo operations are generating more data than ever before, yet airlines are still struggling to make sense of it all. Even with the latest digital tools and innovative solutions, the sheer volume of information can easily overwhelm teams. Instead of providing clarity, it often creates analysis paralysis. Without focus, the adoption of AI and predictive tools can stall, even though these technologies could help streamline operations and boost revenue.

“The problem isn’t that there isn’t enough data—it’s the opposite,” said Jonathan Mellink, Head of Sales and Marketing at Rotate. “There’s just so much of it. People need help sorting through it, especially when complex calculations are involved, and they don’t have the time because they’re juggling other tasks. That’s where we step in, handling the complex stuff so they can focus on understanding the impact on their business.

“We always start with the person, thinking about the ideal scenario we could deliver for them. Technology isn’t there to replace people. It’s there to make them more effective. The goal is to get them out of Excel and in front of customers, doing the work that really matters.”

One of the biggest contributors to this overload is overcomplicated dashboards and reporting tools. Airlines can produce thousands of data points every day—load factors, routes, shipment details—but most of it isn’t immediately useful for making decisions. Without proper filtering, teams struggle to know what to prioritise, which slows down planning and execution. That’s why experts stress the importance of focusing only on the metrics that truly matter.

“We produce an enormous amount of information,” Mellink added. “Even a simple shipment generates countless data points, and the messages we send each day just add to that. What we’re not good at is filtering this to highlight only what’s actually important.

“You can get lost in all the data, just like endlessly scrolling through Instagram, but in air cargo, the stakes are higher. The trick is to surface the points that matter right now for the person using them, while backgrounding everything else. That way, attention goes where it counts.”

Insight over technology

Forecasting and planning in air cargo is becoming increasingly complex. AI and machine learning promise to make predictions more accurate, but Mellink is clear: technology alone won’t get the job done. Human expertise remains crucial. Combining experienced professionals’ knowledge with AI models allows airlines to interpret trends, anticipate capacity changes, and adjust strategies quickly. It’s especially important when unexpected disruptions arise, such as sudden airspace closures or shifts in passenger and freighter schedules.

“We’re not at the point where we can just ask AI what capacity an airline will need in December 2026,” Mellink said. “We combine business knowledge—which is often more reliable than AI at this stage—with models that learn from historical data. That way, forecasts are informed by both experience and technology.

“Business knowledge tells us what’s likely, while AI reveals patterns and probabilities. Neither works perfectly on its own, but together they give actionable insights. This helps us stay flexible and respond to changes quickly.”

Air cargo professionals are keeping a close eye on three main areas: demand trends by verticals, freighter deployments, and order books for future capacity. Accurate insights in these areas inform route planning, fleet allocation, and customer service strategies. Scenario planning has also become a must. Preparing multiple potential outcomes ensures airlines aren’t relying on a single forecast, making it easier to adapt when surprises hit.

“Scenario planning is essential,” Mellink explained. “One forecast just isn’t enough anymore. You need ten slightly different scenarios to see which makes the most sense. Then you can test your plans against each one.

“We also make sure forecasts can be updated quickly, sometimes in just a few days, as situations change. Being nimble is far more effective than trying to predict every possible disruption perfectly.”

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