Artificial intelligence has long been treated as a futuristic ideal, often met with apprehension across industries. But CHAMP Cargosystems is embracing a grounded, structured approach to AI integration—one that prioritises utility, scalability, and ethics.

“What we are doing right now is that, since a few months ago, we launched an AI leadership programme. So it’s a two-year programme,” Lucas Fernandez, CHAMP Cargosystems, head of innovation, explained. “It’s focusing on three aspects. One is bringing AI into our products. We are upskilling our engineering teams and efforts. We are working with vendors like big names such as OpenAI, Microsoft, and other smaller start-ups.”

But the focus isn’t just on the tools—it’s also on the people who use them. “We are upskilling and looking at it from inside, improving our own process,” he explained. “And the last one, to answer the fear around AI, is a lot of governance on AI, a lot of ethics. So, properly checking vendors, putting in place the right process and addressing it.

“It’s more about people getting better jobs, more interesting tasks, less mundane,” he says. And with structured AI deployment, the results are becoming tangible.

Proving ground

AI might still be in its infancy in cargo, but CHAMP is already translating innovation into action. One of the most compelling examples comes from a recent 24-hour IATA ONE Record Hackathon—an event where rapid prototyping meets real-world application.

“We won by designing an agent that was helping people in the field to do assessment of damage on ULDs,” Fernandez shared. “Usually people are doing the assessment, and they tend to be very cautious… and report the ULD for repair too early, while they could still be airworthy.”

CHAMP’s solution? A smart AI tool that interacts via pictures and audio with personnel on the ground to conduct accurate, field-based assessments. “That’s just a direct, tangible example of something that is going to production… and it can be applied to many other types of use cases.”

Beyond inspection, CHAMP is actively exploring AI’s value in automating documentation and customs procedures. “We have a lot of data, but it’s very messy because it’s coming from manual input,” he stated. “We can apply AI to fill the gap… help to classify customs declarations, help to fill missing fields in declarations.

“What’s great about hackathons is that they give you a platform for experimentation, failing and learning very fast,” he says. “But it’s not production-ready… then it takes a lot of time to bring it to maturity.”

Unlocking progress

If AI is the tool, then collaboration is the engine driving its adoption. Fernandez underscored that real innovation depends on a willingness to break out of traditional silos and work collectively across stakeholders.

“It’s an industry that is very community-driven,” he expressed. “We see it coming more and more. Our customers are more and more asking for experimentation and use cases that are around working together.”

This shift towards shared data ecosystems is already being catalysed by IATA’s ONE Record initiative—a common data model aimed at harmonising cargo data flow. “I have the feeling that since a few years ago, this period of collaboration is kind of increasing,” Fernandez reflected. “And maybe there is starting to be a shift in perception into the importance of data sharing.”

ONE Record is “a great enabler of innovation,” Fernandez explained, paving the way for faster access to real-time, clean data—essential for next-generation applications. As more organisations adopt common standards, the friction in deploying AI and automation tools is likely to decline.

“There are a lot of existing legacy systems still in use across the industry… Plugging an AI into a 25-year-old system is coming with its own set of challenges,” he commented. “There are plenty of patching and technologies like robotic process automation… but newer systems will definitely help.”

AI and standardsation

“AI will play a huge role for the next five to ten years,” Fernandez predicted. “We are really at the beginning of the story.”

That journey will likely mirror other major technology waves. “It’s like when we started to introduce computers into our society… It took us a really long time before we really realised the full benefit,” he stated. “Now it’s about stabilising a bit… How can we infuse it into our operation, into our product, so we understand how it works well?”

The road to full-scale digitalisation will also require systemic modernisation—both in terms of platforms and thinking. “We need better digital efficiency, better data quality,” Fernandez emphasised. “It’s about being able to automate the job, to focus on what matters.”