Transport and logistics leaders face the continual challenge of optimizing efficiency and safety, even as their operations become more complex and heavily regulated. Freight volumes remain high and customer expectations continue to rise. Eurostat reported that EU road freight transport reached 1,869 billion metric ton-kilometers in 2024, while rail freight transport reached 375 billion metric ton-kilometers. The industry depends on vast, interconnected networks where precise, effective planning and operations are the key to success.
At the same time, the industry is dealing with ongoing labor shortages. In 2025, IRU reported that 426,000 truck driver positions were unfilled in Europe. It also warned that more than a third of drivers are over 55, while only 4% are under 25. By 2029, around 550,000 truck drivers are expected to retire. Similar observations can be seen in the rail sector. Around half of all operational employees in the German rail industry are expected to retire by 2030, according to the projections of Allianz pro Schiene and VDB, the German Railway Industry Association. This is not a German challenge alone. Across Europe, rail enterprises are reporting the same growing difficulty: an aging workforce approaching retirement, with too few younger workers coming through to replace them.
To overcome the challenges, industry experts like Dr. Olaf Radant, Principal at Eraneos, see AI as a viable path forward. But what does effective implementation look like, especially in safety-critical operations?
Filling the labor gap
In many parts of transport and logistics, especially rail, labor shortages have been a long-time challenge. Many organizations now see real potential for technology to help close the gap and support safe, efficient operations.
Radant believes the sector now has a clear opportunity to respond to these long-term workforce pressures in smarter ways. “The sector uses practical tools to reduce avoidable strain, improve decision-making, and help experienced workers apply their knowledge where it has the greatest impact. That can make work more manageable and strengthen the entire organization’s resilience,” he says.
In this context, labor or skills gaps can actually help guide your AI strategy. “Look for the areas where your organization is lacking human workers or skills. Those are often where the biggest opportunities for AI deployment are. If your workshop is understaffed, for example, you can probably benefit quickly from using predictive maintenance tools and switching from a reactive maintenance approach to a more proactive strategy,” says Radant.
"The real challenge lies not in the technology, but in the transformation. And like any real change, this begins with a clear decision: We're going to do this now. And we're going to do it right."
Exploring AI’s operational potential
AI can already improve safety and efficiency by automating many repetitive, time-sensitive, and error-prone tasks that have traditionally required manual labor. In road freight, that means monitoring driver hours and rest periods, or checking route changes and dispatch data to identify fatigue or compliance risks earlier. In rail, it means predictive maintenance, disruption support in dispatch and sensors or cameras on trains inspecting the network while passing through it. In administration, it means validating shipment data, identifying documentation errors and supporting predictive procurement. In network planning, it means predicting changes in order volumes, lane demand, trailer and driver availability, and depot capacity.
Radant describes AI’s operational potential: “The most valuable tools are the everyday systems and switches that flag problems weeks in advance, sensors and cameras on trains that inspect the network as they move, and dispatching tools that help you make decisions based on what’s best for the network, not just for one department.”
Embracing a change mentality
So how can organizations set up their AI initiatives for success? A major factor, Radant says, is laying a strong cultural foundation for change within the organization.
“It’s important for organizations to start with a mindset that embraces experimentation and learning through doing. Instead of treating safety as a reason not to try new approaches, we can start building more trust by focusing on use cases where AI and other technologies are proven to support safer operations,” he says.
Replace? Or empower?
In both cases, value is only created when strategy, people, and technology move together. Learn how we help leaders make AI work.
Learning by doing
Radant emphasizes the importance of embedding AI initiatives in practical operations from the early stages of implementation. “Look for ways to incorporate AI directly into environments where they need to work, like workshops, dispatch settings, approval processes, and frontline routines,” he recommends.
An effective approach is to start with a narrow, clearly defined problem where the operational value is easy to see. Projects also require clear ownership, realistic scope and early involvement from the people who will actually use the tool. “Start with an open mentality, knowing that useful systems rarely arrive fully perfected from day one. They improve through use, observation and correction,” says Radant.
"Today's leaders must be able to do more than just organize. Leadership is needed that embraces uncertainty, creates clarity, and builds culture — because that is precisely what will make the difference between AI implementation and true transformation."
The opportunity to move forward
For many transport and logistics firms, the bigger challenge now is making sure they are ready to benefit from AI as the market continues to evolve. Freight demand remains high. Labor shortages in rail and other industries continue. Experienced workers are retiring. Networks are becoming more complex. Compliance requirements are also increasing. At the same time, these pressures are giving firms a stronger reason to invest in better tools, stronger processes, and more resilient ways of working. “In today’s market, taking action creates real advantages. We see that firms that move early can strengthen resilience, support productivity, and build trust over time,” observes Radant.
“What we need is a different attitude: get out of the sleeper car and into the high-speed train. We must show the courage to at least try things, even if they aren’t perfect right away,” he says.
