The airfreight and logistics industry is currently experiencing a disruption comparable to the digitalisation shift of the past. At that time, many questioned the need for digital transformation, insisting that their on-premises systems were sufficient and that manual processes were adequate.

For companies aiming to be industry leaders—especially those developing software as a service (SaaS) solutions—this is a critical moment of disruption. This shift extends beyond just business applications; it affects the entire IT landscape within airfreight and logistics. While business applications may be the most visible area of transformation due to increasing demands for efficiency and optimisation, the impact reaches every part of the industry.

The true advantage of this transition lies in the new opportunities it creates—capabilities that were previously unattainable. This is why it is crucial for businesses to carefully evaluate the potential and strategic benefits of this change. Those who recognise and embrace this shift will set the pace for the future of airfreight and logistics.

“It really comes down to trust—just like with any other major shift. Adoption happens when capabilities are clearly understood and the value is evident. We see this in our own toolset as well,” Salvatore Lombardo, Chief Product and Technology Officer at Coupa, stated.

“There are two key aspects to trust. First, end users need to believe that these new tools will actually help them in their daily work. Many still have doubts, and that’s why it’s essential not only to deliver capabilities but also to explain their value—why they matter and how they can improve efficiency.

“The second aspect is trust in AI-driven decision-making. With generative AI and advanced models, users often wonder, “Where is this information coming from?” If businesses can’t trust that the recommendations and insights provided by these tools are reliable, adoption will be slow.

“That’s why, when designing our products, we focus on transparency. For example, if our system recommends an optimised transport route based on multiple factors, we ensure that users can see exactly how the AI arrived at that conclusion. Even when pulling insights from external datasets, providing clear explanations builds confidence.

“Ultimately, that’s the key to successfully driving AI adoption—especially in the early stages of this technological shift. If customers trust the capabilities, they’ll embrace the transformation.”

Real world application

There are several concrete, real-world examples that highlight the impact of a strong solution offering. In the airline industry, Coupa’s solutions have gained significant adoption, currently serving 50% of Fortune 500 airlines—a substantial level of coverage, with Lombardo citing two key examples of how they have optimised operations.

“The first example involves a major airline in America. This airline was struggling with over 20,000 legacy vendor contracts scattered across various systems. Managing these contracts manually—searching through shared files to determine their status—was an inefficient and time-consuming process,” Lombardo explained.

“When they implemented Coupa’s Contract Lifecycle Management (CLM) solution, all contracts were uploaded and scanned using AI-driven summarisation. This dramatically accelerated their ability to assess contract terms, track key clauses, and determine whether contracts were still active. From there, they could seamlessly connect this information to sourcing events and supplier management—a critical step in improving efficiency. This was their starting point, and it’s a great example of turning AI discussions into real-world applications.

“Another example I love to highlight is Finnair, one of our standout customers. By implementing Coupa’s AI-powered invoice processing solution, they reduced invoice processing time by 50%. The AI-driven scanning mechanism transformed their previously manual workflow into a fully digital, automated process. The system not only scanned invoices but also matched them against purchase orders and facilitated payments, significantly improving speed and accuracy. Finnair is incredibly proud of this transformation, and honestly, I’m just as proud to share it.”

Replacing roles to improve operations

It is clear that there are roles that machines will replace. For example, tasks such as data matching and invoice approvals are obvious candidates. The 50% reduction in processing time is a clear example—it’s not just about system efficiency; it’s about reducing manual work. Less manual work means fewer people are needed for those tasks, which enables them to focus on more strategic aspects within the company.

It’s not only about increasing trust and efficiency, but also about aligning with the goal of building solutions for buyers and suppliers. The key here is autonomy—systems that are intelligent enough to perform these tasks without human intervention.

“Imagine a future where buyer and supplier agents can negotiate directly with each other, based on predefined constraints, without the need for human sourcing specialists—at least for non-crucial items initially. “The future isn’t far off – Coupa’s Agentic AI is already enabling businesses to automate sourcing of non-critical items, freeing up procurement teams to focus on strategic decisions. By leveraging AI-driven negotiation, businesses are reducing manual workload and accelerating procurement cycles.  This is something that the company is working toward, as it makes the process more efficient, and with trust in the development of the technology, they can be confident that it will be executed correctly,” Lombardo expressed.

Additionally, there is the political dimension to consider, particularly with how quickly businesses need to react to geopolitical situations. Take sourcing as an example. As trade policies shift and tariff landscapes evolve, businesses must rapidly adapt their sourcing and procurement strategies. The ability to quicly scenario-plan and shift supplier networks will define market leaders in this new economic climate. Given current global events, many companies need to quickly adjust their supply chains due to factors like tariffs.

A large client in the frozen food industry, for example, operates globally in a manner similar to airlines, which function from multiple locations. In industries like this, having an automated and autonomous sourcing network is crucial. Without it, companies risk falling behind their competitors. While they may still be capable, speed is essential in today’s world.

“The faster a company can adjust its sourcing network, the higher its chances of succeeding or growing. This flexibility and responsiveness provide a competitive advantage, which is why it’s critical to embrace autonomous solutions in today’s environment,” he added.

Accurate forecasting

For an airline, one of the most obvious challenges is understanding and forecasting demand—how full is a plane going to be on a certain route, do they have enough demand at a specific airport, etc

AI can help address this by enabling different systems or agents to communicate with each other. In this context, AI agents play a key role. For instance, an airline might use an AI-driven demand generation tool to forecast how many passengers are likely to book on a specific flight. However, simply knowing the demand isn’t enough to close the loop effectively. It’s also crucial to understand the reasons behind it.

“Imagine connecting the demand generation tool to a sourcing engine like Coupa, which also uses AI to optimise sourcing locations,” Lombardo stated. “With this connection, the AI can automatically determine the right suppliers, at the right price, and in the right location, ensuring the airline has the necessary items at the right time. This is where Coupa’s value proposition shines—automating and optimizing processes to reduce inefficiencies.”

“In addition to demand forecasting, there are also internal optimisation opportunities within an airline, such as streamlining invoicing or handling non-PO (purchase order) spend. AI-powered solutions like Coupa can help reduce costs in these areas, improving efficiency. By addressing wasteful spending—whether through better management of invoices or by switching to catalog-based purchasing over off-contract spending—airlines can reinvest that saved capital into more strategic areas. For Chief Procurement Officers (CPOs), this allows for more flexibility in how resources are allocated, without necessarily having to return savings but instead redirecting funds where they are most needed.

“Whether it’s forecasting demand, optimizing sourcing, or reducing waste, AI solutions like Coupa can help airlines operate more efficiently and effectively, which is crucial in today’s competitive environment.”