On a scale of one to ten, the air cargo industry is currently at just three when it comes to adopting AI-assisted decision-making, said Cédric Millet, president of industry tech firm CargoTech.
He says that AI (artificial intelligence) is only sporadically used in different segments of the industry – mostly in customer service and engagement functions, because these have the greatest similarity to processes in other, more digitally-developed industries. Much of the sector is still in the process of digitizing its operations and starting to accumulate data volumes. “To embark on the journey of AI-assisted decision-making, it is crucial to extract a large volume of data to train the models and to identify anomalies for better decision-making, going forward,” Millet explains.
Data is currently heavily fragmented across stakeholders, leading to huge inefficiency. However, AI could synthesize data across the supply chain, promoting better end-to-end visibility and decision-making.
In fact, argues Michael Teoh, head of strategy at CargoTech, the air cargo industry faces the challenge of an abundance of data. “For a long period, the air cargo industry suffered from data scarcity, when it came to advanced data analysis. As data availability increased, Business Intelligence (BI) dashboards proliferated, sparking enthusiasm about the possibilities of applying Artificial Intelligence (AI) to revolutionize air cargo operations. However, there’s often a misconception that AI, in itself, will be able to solve some of the industry’s biggest challenges.
“Experience has shown that AI does not replace the need for commercial teams to devise innovative use cases that drive value through better decision-making. AI should be viewed as an enabler rather than an end goal.”
The cargo charter niche faces the greatest challenge when it comes to data availability and quality: Currently, crucial data is held within emails, messages, and analogue channels. These analogue formats first have to be digitized before introducing AI-enabled tools.
AI will benefit carriers operating cargo charters in long-term planning. Airlines operating both scheduled flights and charters want to know how much of their fleet they should make available for charter, what the peak charter lanes could be, and then weigh up of selling charter capacity compared to keeping the aircraft on a scheduled programme. With the right amount of market data including common routings, commodity types and market verticals, AI can help find the optimum balance, offering aggregated market intelligence that supports longer term planning.
Carriers also want to make informed decisions on which aircraft and routing within their network would be the best fit to maximize on available capacity. By combining historical internal data and request data within a machine learning model that learns past behaviours and patterns, AI could provide relevant information for charter salespeople on which to base their quotation decision.
AI not only offers commercial decision-making benefits, but also opens up development opportunities. “There is often the misconception that AI leads to a reduction in employees,” states Cédric Millet. “At CargoTech, we believe that roles will not be replaced, but specific tasks within them may change.”
For example, sales staff will be relieved from having to spend time analysing data and trends to finding new customers. AI can identify sales leads and enable the salesperson to spend more time with each customer. “AI will reshape roles to meet evolving needs, thus ensuring sustainability and empowering employees as they focus on strategic work and are encouraged to upskill with new tools,” he predicts. Through the automation of repetitive tasks, AI helps streamline processes, reduce errors, and enhance efficiency.
Also: “Cutting-edge technology attracts younger generations to the industry,” he summarizes – an important point in an industry that has long struggled to fill open positions.
