How widespread is the use of AI in freight transport? IRU examined the implementation of AI and the key market trends facing the industry at the Transport Logistic conference in Munich.
Industry experts and investment decision-makers visited Munich, Germany, this week to attend the Transport Logistic, the world’s leading trade fair for logistics, mobility, IT and supply chain management.
The IRU, the world’s road transport organisation, presented the latest industry developments at an event organised by Upply during Transport Logistic.
Capacity and demand, cost inflation, decarbonisation, driver shortages and the adoption of technology – five interlinked trends – are increasingly impacting the profitability, efficiency and sustainability of transport and logistics.
Vincent Erard, IRU Senior Director of Strategy and Development, said: “The truck driver shortage is a serious challenge facing our industry and is putting significant pressure on road transport capacity. We estimate that there are 426,000 unfilled truck driver vacancies in Europe today, and the situation is only getting worse.”
“With more than a third of drivers over 55, around 550,000 truck drivers are expected to retire by 2029. This wave of retirements is unlikely to be fully offset by new entrants to the profession,” he added.
Few young people or women are entering the profession – only 3.2% of drivers are women, and only 4% are under 25 – due to difficult work-life balance conditions, inadequate rest facilities and harsh treatment at delivery locations, among other things.
“The strain caused by the worsening driver shortage will be exacerbated by the growth in freight volumes, which are forecast to grow by 9% by 2030, putting even more pressure on transport capacity,” stressed Vincent Erard.
Freight transport also faces high cost pressures. For example, the total cost of ownership (TCO) increased by 24% in Germany, Europe’s second largest road freight market, between 2021 and 2024.
The increase in TCO was driven by an 83% increase in toll rates in 2023 (mainly due to CO₂ emissions), a 19% increase in fuel prices, a post-COVID wage increase, a shortage of drivers that has increased bargaining power, and a near doubling of truck prices over the past decade due to stricter emissions standards, safety regulations, and inflation.
Decarbonization is putting additional pressure on road transport operators. Most policies penalize operators that rely on diesel trucks (e.g. CO₂ standards, Eurovignette, ETS2), although support incentives remain limited. Enabling conditions such as network capacity, infrastructure and biofuel supply are lagging behind, hindering a widespread shift to alternative powertrains.
“It’s simple: operators are not getting the decarbonisation support they need to move to low and zero-emission vehicles,” said Vincent Erard.
At the same time, road transport is undergoing a major technological transition, driven by advances in automation, electrification, data analytics and connectivity. All of these have the potential to significantly ease the industry’s challenges. Artificial intelligence is emerging as a key driver of this transformation.
The IRU surveyed over 500 operators in 19 EU countries to explore the use of AI.
Almost 90% of small operators (with fewer than 49 employees), which account for 98% of EU road transport companies, do not use AI. Among companies with more than 50 employees, 12% are now using AI solutions.
The main reason for the low adoption rate: AI is not seen as a priority. Other IRU research shows that the main challenges for operators remain driver shortages, rising costs and regulatory compliance.
“It is logical to conclude that many companies do not yet see AI as a direct solution to improve efficiency or reduce costs,” said Vincent Erard. “The second most frequently mentioned barrier was financial. The initial investment in technology, infrastructure and personnel is considered too high.”
“It is worth noting that the two leading use cases for AI, route optimization and predictive maintenance, not only reduce costs but also support reliability and fuel efficiency,” he added.
Even at this early stage, AI solutions are delivering concrete value. While successful implementation requires investment and change management, solutions are increasingly being designed to integrate with existing systems, making wider adoption more feasible.