The Capacity Code: What Freight Forwarders Can Learn from Passenger Airlines

In passenger aviation, a concept called code-sharing is so common we barely think about it. You can book a ticket with American Airlines, fly the first leg on a British Airways jet, connect on a Virgin Atlantic route, and still enjoy a seamless itinerary. The customer benefits from more options, the airlines fill more seats, and everyone wins.

Air cargo is another story entirely.

“On cargo, that doesn’t happen very often,” says Chris Condon, Founder and CEO of Aircon AI. “Each airline is kind of out for their own. Origin controls the rates, and the destination often doesn’t see the buy rates. There’s a lot of protectionism.”

That protectionism, coupled with siloed systems and manual processes, means planes often depart with empty cargo space—while other flights on similar routes are overbooked and delayed. It’s an inefficiency that costs freight forwarders, shippers, and carriers millions every year.

Evergreen Capacity: Use It or Lose It

Cargo space is a perishable asset. Once a flight leaves, that capacity is gone forever.

“The airlines’ capacity is evergreen,” Condon explains. “Once that plane leaves, that capacity is out of the market. If you’re not utilizing it, it’s a lose for the airline, a lose for the freight forwarder, and a lose for the buyer.”

Compare that with the passenger side: airlines actively work to avoid flying empty seats. They overbook based on predictive models, sell blocks of seats to travel partners, and swap passengers across alliances to smooth demand. The objective is simple—maximize revenue per flight without hurting the customer experience.

Cargo doesn’t have an equivalent system at scale. That’s the opportunity Condon believes could transform freight forwarding.

The Business Case for Cargo “Ride-Sharing”

In today’s environment, forwarders compete to secure the best rates and the most reliable capacity. If one carrier offers $1.00 per kilo while others are at $1.50, the cheapest option gets flooded with bookings. Congestion builds, flights are delayed, and suddenly, that “deal” creates downstream costs for everyone.

“The plane that’s empty is still flying,” Condon points out. “How can we… rideshare, for lack of a better word? The AI can predict that.”

An AI-enabled system could anticipate no-shows, match underutilized routes with excess demand, and dynamically reallocate shipments across carriers—much like passenger alliances do. This wouldn’t just be a revenue play; it would:

Reduce missed connections and costly exception handling.
Stabilize transit times and service levels.
Lower environmental impact by increasing load factors per flight.

For shippers, it could mean fewer delays and more routing options. For forwarders, it could mean better margins without squeezing carriers. And for airlines, it could mean more predictable, profitable use of their fleets.

The Obstacles: Trust, Data, and Culture

If the upside is so clear, why hasn’t this happened already? Condon doesn’t mince words.

“It’ll take people working together—ground handlers, airlines, airports—to really streamline that. It’s not just the tech. The tech is cool and does a lot of things, but we gotta figure out a way to stay in your swim lane and have the common goal of making air freight fluid.”

The barriers are more cultural and structural than technological:

Protectionism: Carriers guard rates and capacity data as competitive assets.
Fragmentation: The industry is a patchwork of booking platforms, rate repositories, and manual processes.
Trust Gap: Forwarders and airlines often have transactional relationships rather than strategic partnerships.

Breaking through these barriers requires not just software integration, but also new commercial agreements, shared KPIs, and possibly industry-level governance.

AI as the Enabler, Not the Driver

Condon is clear-eyed about the role of AI. Technology alone won’t fix this. It’s a tool to facilitate smarter decisions, not a magic wand.

In Aircon AI’s model, machine learning could aggregate data from multiple forwarders, identify consistent traffic patterns (like “five customers going Dallas to London every Thursday”), and negotiate consolidated blocks with airlines. The savings could be distributed across participating forwarders, and the carrier gets guaranteed volume.

“The benefit to the airline is every Thursday they know they are gonna get this amount of freight, which is more important to them than the five to 10 cents difference in the kilo rate,” says Condon.

It’s essentially the code-share model for cargo—enabled by AI, sustained by human agreements.

The Sustainability Dividend

Beyond profit and service, there’s an environmental imperative. Aviation is a carbon-intensive industry. Every kilo of cargo moved more efficiently reduces emissions per unit shipped.

You don’t need to be in ESG reporting to see the PR and compliance upside. Large shippers are under increasing pressure to measure and cut supply chain emissions. Being able to point to collaborative capacity utilization as part of that strategy could be a differentiator in bids and renewals.

What Leaders Should Be Asking Now

For executives in manufacturing, logistics, and distribution, this conversation isn’t just for carriers and forwarders. The ripple effects of wasted capacity hit your P&L in the form of delays, surcharges, and inventory imbalances.

Here are three questions worth asking your teams and partners:

Where do we see wasted capacity today? This might be in booked-but-unused allocations, poorly utilized consolidations, or lanes that consistently run hot while others have slack.

What’s our data visibility on capacity? Without accurate, timely data, any load-balancing strategy is guesswork.

Who could we partner with? Strategic alliances with other shippers, forwarders, or even competitors could open access to better rates and more reliable service.

A Pilot, Not a Revolution

It’s tempting to think of this as an all-or-nothing transformation. In reality, leaders could start small:

Identify one or two key lanes with chronic over/under-utilization.
Work with forwarders and carriers willing to test data sharing.
Use AI-driven forecasting to propose weekly consolidated blocks.
Track KPIs: load factor, on-time delivery, cost per kilo, exception events.

Even modest gains on a pilot lane can prove the concept, build trust, and generate the momentum for broader adoption.

The Leadership Play

In a market that often rewards short-term wins—like grabbing the cheapest rate—it takes vision to invest in structural efficiency. Passenger airlines embraced code-sharing because it improved profitability and customer experience over the long haul. Cargo can do the same.

“The idea,” Condon says, “is to provide the best solution to the freight forwarder as possible. I don’t care if we move it or not. I care that you win the business as a freight forwarder.”

That mindset—prioritizing mutual wins over zero-sum games—is exactly what it will take to crack the capacity code.