More than a buzzword: AI’s growing role in air cargo

The air cargo industry is increasingly turning to AI for digital booking and pricing optimization, flight information based on real-time data, operating efficiencies and more. [caption id="attachment_57134199" align="alignright" width="300"] (Photo/Air Cargo Next)[/caption] AI implementation and use cases were omnipresent at the World Cargo Symposium (WCS) in Hong Kong last month. Symposium attendees avidly engaged with Air Cargo Next to discuss the current state of AI, its future in the industry and what’s required to leverage the technology to its fullest capabilities. Unlike “blockchain,” the tech buzzword that came before AI, there is a bigger place for the technology in air cargo. “Our responsibility will be to take that buzzword and turn it into something,” Yuval Baruch , CEO of Hermes Logistics Technologies , told Air Cargo Next . “‘Cloud’ was the buzzword; ‘big data’ was a buzzword. And then we gradually turned that into something that is concrete, implementable, usable,” he said, referring to AI. Current, future use cases AI can streamline operations that currently require multiple emails, phone calls and manual data entry. For example, the tech can extract data from emails and populate forms with it. This AI-driven automation is what “customers are asking for most of the AI functionality today,” Scott Sangster , general manager at logistics technology provider Descartes Systems Group , told Air Cargo Next . “There’s a lot of focus right now from our customer base to just use [AI for] data automation.” Meanwhile, technology products provider Kale Logistics Solutions is using AI in its truck slot-booking platform, which optimizes cargo loading and offloading at airports. Suneet Gupta , vice president and global head of cargo community systems at Kale, told Air Cargo Next that the AI determines “what kind of cargo is coming, and what type of container, what is the size of the truck. And it estimates how much time does it take to load/unload the cargo. Then it uses its import machine learning layer on top of it, an algorithmic layer, that calculates and recalculates the slot timing so that the slot utilization is optimal.” “As we go forward, AI is going to play a very pivotal role, but you have to clearly define the use case.” — Suneet Gupta, vice president and global head of cargo community systems at Kale Logistics Solutions AI can also help create solutions in the event of a problem, such as lost or delayed cargo. “AI in the future can be [used] as a personal assistant for the cargo, kind of like consumer service, which will act as a guardian angel,” Awery Aviation Software Chief Executive Vitaly Smilianets said in a WCS session. “If the AI can see that the first sector is delayed or cargo was offloaded, it can proactively offer or even do the rebooking process.” Descartes is also looking into AI’s predictive capabilities, Sangster said. [caption id="attachment_57142616" align="alignright" width="412"] Speaking at WCS are, from left, Anna Ghion, senior global account manager for Amazon Web Services’ MNO AIR; Ingrid Lee, head of cargo digital at Cathay Cargo; Elena Sanguino, product manager at Revenue Technology Services; and Sabari Ramnath, senior manager of solution management and enterprise computing solutions at UNISYS. (Photo/Air Cargo Next)[/caption] “We’re asking, ‘How do we use this to predict challenges that you might have in your supply chain or recommend better trade lanes or better methodologies to deliver the goods?’” Sangster said. “The next generation of AI is starting to make more of those suggestions.” Hermes’ Baruch said AI is sprinkled into many of his company’s solutions, even when it is not necessarily referred to as such. “If there is a backlog or if there is, let’s say, a problem with certain shipments , the service management tools that recommend how you recover … is AI,” Baruch said. “I think that will become a lot more intelligent with much better data-processing capabilities.” There are likely more use cases that have not been considered yet. “AI is a buzzword; everybody is using AI,” Gupta said. “It's quite possible that in the future AI may be much bigger than we are thinking right now.” Data collection and privacy AI requires comprehensive collection and availability of data, which it analyzes to predict disruptions, determine efficiencies and offer accurate services. “AI will be really useful as more and more logistics companies and airlines [realize the] value of data,” Awery’s Smilianets said. “So, having all the data, AI can help to make a better prediction, better utilization of the equipment, make better processes.” The air cargo industry must continue digitizing records and digitalizing processes to collect enough data for AI to be used effectively, Jean Verheyen, chief executive of technology provider Nallian , told Air Cargo Next . “Today the industry is still paper-based and manual, [so] AI cannot do a lot. AI will accelerate and augment the possibility to explore the data you have. But first you need to have the data digitally.” — Jean Verheyen, CEO of Nallian Compiling data from multiple stakeholders would enhance the reach of AI across the industry. “We want to create some kind of milestone plan where every step in the chain can be monitored, where you have visibility across the entire supply chain,” Davide Scatorchia , business development and optimization manager at Air Cargo Belgium , said at WCS. “The data that we have right now is not, let’s say, smart. It’s not doing any calculations on its own. “But AI ... is something that we want to have to be sure that data-driven decisions can be made automatically,” he said. However, since data is company property, many companies are concerned about sharing data that could be used by competitors. [caption id="attachment_57139462" align="alignright" width="300"] (Photo/Canva)[/caption] Platforms like ChatGPT are open, meaning that all data put into the system becomes public. However, AI use in the air cargo industry is typically on a closed system, Hong Kong Air Cargo Terminals Ltd. (Hactl) Chief Executive Wilson Kwong told Air Cargo Next . “As the cargo handler or ground handling agency, we are subject to all kinds of data privacy requirements as mandated not just by the airlines’ customers’ concerns, but by the regulatory authorities,” Kwong said. “We always try to use technology, but there has to be a limit and there has to be a very fine balance.” A closed system could have multiple users, so data privacy must be prioritized, Descartes’ Sangster said. “A customer’s data is theirs to control and to dictate to us who we share that information with, even just down at the master air waybill,” he said. “When we look at some of our [business] partners in AI, we look for partners that are approaching it the same way and are not generalizing data across multiple customers of theirs to learn.” [caption id="attachment_57137837" align="alignleft" width="300"] (Courtesy/CanStock/itchaznong)[/caption] To protect data privacy, stakeholders should decide early on how data will be used when building an AI model. “Is the data that you’re ingesting then also being used to train the AI?” Moritz Claussen , founder and co-chief executive of digital booking platform cargo.one , questioned. “And then, does it become part of the model? And I think it depends on the way that you structure it,” he told Air Cargo Next. “Obviously, there are ways to make sure that the data stays within an enclosed environment,” Claussen said. “You might want to train the AI on that data for your own purposes, but you might not want to try to pull out a model that is applicable or available to everyone on that model.” “We obviously need to make sure that contractual obligations and clauses are all in place, and we ensure that security. It’s not just a blank check for open AI or anyone training these models to use the data that you give them.” — Moritz Claussen, co-founder and CEO of cargo.one Education at all levels Projects implementing new technologies often fail because they do not have buy-in across the leadership team and because the company sets unrealistic goals, Elena Sanguino , product manager at Revenue Technology Services , said at WCS. [caption id="attachment_57135591" align="alignright" width="300"] (Photo/CanStock/buchachon)[/caption] “It’s key to not only educate yourself, but to also have your executive teams have a level of understanding of what is said about the technology, what are the capabilities, what are also the limitations. Because that is going to help set those realistic expectations that are going to get people interested and motivated to continue working on the project and to actually get it to fruition,” she said. Approaching new technology with an open mind and a willingness to ask questions is vital. “Not everyone understands everything, especially on the technical side,” Ingrid Lee , head of cargo digital at Cathay Cargo , said in a WCS session. “But if we can actually trigger interest for people so that they can understand the potential benefit from the business angles ... that’s how we get a conversation going so that they will actually be more willing to understand further about AI.” “In order to keep up with the new knowledge, we really need to be humble.” — Ingrid Lee, head of cargo digital at Cathay Cargo AI implementation is not synonymous with employee utilization, consultant Jeff Pan said at WCS. Pan is the former chief product officer at Teleport , AirAsia ’s air cargo venture, and is a co-founder of Belli AI , which helps airlines digitalize operations. [caption id="attachment_57142613" align="alignright" width="255"] Jeff Pan, former chief product officer at Teleport and co-founder of Belli AI, speaks at the World Cargo Symposium. (Photo/Air Cargo Next)[/caption] He advises in-person training rather than video training, and to involve employees at all levels in the training. “I would watch and track the retention rates on video training — it does not work,” Pan said. “We also experimented between external trainers and internal trainers and I think I can also conclusively say that internal trainers, even if it’s a junior employee in your organization, are far more impactful than external trainers.” When organizing AI training, Pan said companies should: Create a dedicated learning team to coordinate the content and trainers; Have junior and senior employees alike learn the system; and Make the transformation leadership-driven, from top to bottom. The junior employees “ended up becoming the junior trainers,” Pan said. “They started breaking down the data silos across different organizations, because a lot of these trainings were done cross-department, cross-functional. Their presentation skills actually became phenomenal. And it wasn’t a coincidence that the early junior trainers ended up having very high career velocities.” Once an AI system has been implemented, the company should track its use to see which departments are “lagging” and which are “following through,” Pan said. AI supports the workforce AI can also be a draw for new talent . “We hear a lot that it’s quite hard to get new people or new students in the air cargo industry because it’s a lot of monotonous work, a lot of repetitive tasks,” Awery’s Smilianets said. “AI just brings more interest and makes work in cargo even more enjoyable. “AI, in any case, is not replacing humans,” he said. “It does make the work more efficient and more beneficial.” Michelle Lawrence , director of marketing at Airlines Services International , agreed in an interview with Air Cargo Next that AI will not replace people. “It means that you don’t have to spend an hour writing a brief or anything like that. Use it when you can, but you also have to be cautious with that kind of stuff. You double-check it. Humans still matter.” — Michelle Lawrence, director of marketing at Airlines Services International AI could even create new positions, according to Anna Ghion , senior global account manager for Amazon Web Services ’ MNO AIR. “AI won’t replace workers, but rather create new possibilities,” Ghion said in a WCS session. “Nowadays, 60% of the jobs we do today didn't exist in 1940. ... Innovation is helping to create new jobs.”

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