The air cargo industry is still moving forward on the runway of AI opportunities. Leading technology group CargoTech already offers products to ensure a smooth technology take-off, with AI serving as the fuel for sound business decisions. Cédric Millet, President of CargoTech, and its members explain the ways in which the group is leveraging artificial intelligence to support decision-making and clear up some of the myths surrounding the technology.
“On a scale of 1 to 10, I would say the air cargo industry is currently ranked 3 when it comes to adopting AI-assisted decision-making,” says Cédric Millet, President of CargoTech. AI is being used sporadically in various sectors of the air cargo industry – mostly in customer service and engagement functions, because they have the greatest similarity to processes in other, more digitally advanced, industries. Much of the air cargo industry is still in the process of digitizing its operations and starting to collect volumes of data. “To embark on the AI-assisted decision-making journey, it is necessary to extract a large amount of data to train models and identify anomalies in order to make better decisions moving forward,” Millet explains.
Enhance data integration
Data is currently highly fragmented among stakeholders, leading to significant inefficiencies. AI models have the ability to aggregate data across the supply chain, thus enhancing end-to-end visibility and decision-making. CargoAi already offers advanced AI-driven tools that help simplify decision-making for logistics professionals, such as its CargoCOPILOT product: CargoAi’s AI-powered email add-on enables frontline workforces to retrieve dynamic rates directly via their inbox Their own, without having to search across platforms.
Another practical application of AI aimed at enhancing business decision-making processes that has resulted from collaboration with a number of airlines is Rotate’s “Fair Share Analysis” which not only informs airlines of their market position in terms of market share and revenue level, but also Also a crucial element when it comes to optimizing an airline’s network and origin destination (OD) sales mix. Here, AI leverages proprietary capability data and machine learning algorithms, and combines market data to create fair share estimates.
AI is an enabler, not a solution
In contrast to the charter sector, the general air cargo industry faces the challenge of an abundance of data. “For a long time, the air cargo industry has suffered from a scarcity of data, when it comes to advanced data analysis. With the increased availability of data, business intelligence (BI) dashboards have proliferated, sparking excitement about the possibilities of applying artificial intelligence (AI) to revolutionize operations. Air Cargo However, there is often a misconception that AI, by itself, will be able to solve some of the biggest challenges facing the industry. Experience has shown that AI does not replace the need for business teams to create innovative use cases that drive value By making better decisions AI should be viewed as a tool Enabling, not a final goal.
No, the computer isn’t always right?
Wiremind Cargo CargoStack’s suite of digital solutions has been designed with specifically this in mind: Wiremind Cargo models are developed to be accurate and give the best recommendations possible, but there will always be scenarios where the model may not have seen something before, or needs Users to intervene. One complaint about AI is that it often acts as a “black box,” providing recommended outcomes but without explaining how it arrived at the outcome. Wiremind Cargo proactively seeks to improve this: Along with its model recommendations, the CargoStack Optimizer modules aim to transparently share relevant insights to users that explain how the score was generated and allow them to make an informed decision on whether they want to retain or exceed the value (which They are always empowered to do). This is a very intentional approach to product design to avoid the black box problem.
There’s more to AI than ChatGPT
Wiremind Cargo has been implementing and delivering the benefits of AI to the air cargo industry since the company was founded. “It’s important to remember that AI is a very broad umbrella, not just ChatGPT/Generative AI. Wiremind Cargo has successfully deployed machine learning models that help customers make business decisions around capacity and revenue management. Each CargoStack module runs Optimiser uses various artificial intelligence models trained on the customer’s own data and tasked with trying to make specific predictions such as the expected amount of baggage on a flight, the frequency with which reservations appear, or the optimal entry requirement on a flight Machine Learning Models CargoTech solutions are able to process large data sets to identify trends and patterns, allowing the models to replicate what analysts would do at scale.
Analogue to digital is the first step
The freight charter sector faces the biggest challenge when it comes to data availability and quality: currently, important data is kept in emails, messages and analogue channels. These analog formats must first be converted to digital before we can start delivering AI-enabled tools. Aerios’ flagship Carrier app is an important foundation because it facilitates data collection and is a gateway to implementing more value-added AI and machine learning models into the Aerios product suite.
Long and short term planning
AI will benefit carriers that charter cargo flights in two key decision-making processes. Long-term planning is one area: airlines operating scheduled and charter flights want to know how much of their fleet they should make available for charter, what peak routes could be, and the weight of selling charter aircraft capacity compared to maintaining charter flights. Aircraft within a specific program. With the right amount of market data including common paths, commodity types and market segments, AI can help find the optimal balance, providing aggregate market information that supports long-term planning.
The second area is the charter flight quote process: carriers want to make informed decisions about which aircraft and routes within their network will be best suited to maximize available capacity. By combining historical internal data and demand data within a machine learning model that learns past behaviors and patterns, AI can provide rental salespeople with relevant information on which to base their quote decision.
Empower and attract employees
AI not only offers business decision-making benefits, but also opens up development opportunities. “There is often a misconception that AI leads to a reduction in headcount,” says Cédric Millet. “At CargoTech, we believe roles will not be replaced, but specific tasks within them may change.” For example, sales staff will be relieved from having to spend time analyzing data and trends to uncover target customers, as AI can identify sales leads thus enabling the salesperson to spend more time with each customer. He expects that “AI will reshape roles to meet evolving needs, thus ensuring sustainability and empowering employees while they focus on strategic work and encouraging them to improve their skills using new tools.” By automating repetitive tasks, AI helps streamline processes, reduce errors, and enhance efficiency. And there’s another bonus: “Cutting-edge technology is attracting younger generations to the industry,” he sums up — an important point in an industry that has long struggled to fill vacant positions.
