• The Galley
  • Posts
  • Why one size doesn’t fit all in the sky

Why one size doesn’t fit all in the sky

Airlines are leveraging AI and machine learning to better control waste and meet customer demands 📷️ iStockPhoto

A few years ago, a Canadian airline partnered with celebrated Quebec chef Daniel Vézina to create a signature in-flight menu. In Montreal and across French-speaking Quebec, the response was electric. The reaction in Ontario and other parts of English-speaking Canada? Crickets.

It’s a perfect illustration of a simple truth: Passenger tastes aren’t uniform—they’re shaped by factors like culture and geography, reasons for travel, and also by season and even flight time. 

Airlines are well aware that serving up more flexible, varied, and targeted food and beverage offerings can go a long way toward boosting customer satisfaction. From Shake Shack sliders in business class to regionally tailored meals for economy passengers, in-flight meals are a powerful differentiator.

The world’s highest rated airlines, such as Emirates, Singapore Airlines, and Oman Air, are renowned for their creative, gourmet-standard meals. Despite this, many airlines still take a one-size-fits-all approach to catering, often driven by logistical constraints, legacy systems (hello, spreadsheets), and cost pressures.

The good news for airlines and for passengers is that this dynamic is changing.

From guesswork to granular data

At the heart of this shift is the ability to use machine-learning and AI technology to collect and act on real-time consumption data.

“We know what sells, what doesn’t, and on which routes,” says Fernando Moreira, chief experience officer at IFCS, a global leader in flight provisioning software. 

“We don’t even need to know why—the system tells us that this sandwich sells in Quebec City, but not in Ontario. Or that pizza goes fast during spring break, especially with more kids on board. And then it automatically adjusts the food order for that flight.”

This kind of route and season specific insight is very hard to manage manually—often taking an army of planners. But systems powered by machine learning can analyze sales patterns across flights and propose precise, route-specific meal combinations that better reflect actual demand.

The traditional one-size-fits-all approach doesn’t just lead to sub-optimal menu options, it leads to more food waste and lower efficiency. It’s not unusual for airlines to load an aircraft with the same amount of food for a short-haul and a long-haul flight resulting in waste on short flights and shortages on long ones. 

Automating variety

Traditionally, offering menu variety has come at a high operational cost.  Some larger airlines have teams of eight full-time staffers or more managing their menu program. Modern systems can be operated by just one person (a super user)—with far more agility.

Catering teams can make updates from a central desktop, with changes instantly communicated across suppliers, kitchens, and crew. That opens the door to faster seasonal updates, regional customizations, and even partnerships with restaurants or celebrity chefs.

This flexibility is not just a matter of luxury or branding—it creates competitive advantages and real economic value. 

Airlines can expect as much as a 10X improvement in margins and to cut waste in half within months of implementation of such systems.

“The system lets you do what you already know you need to do,” Moreira says. “But without this kind of tool, it’s almost impossible.”

Inflight dining is becoming a key battleground for airlines. But to deliver the necessary variety and quality at scale—without blowing up costs—airlines need better tools.