How AI productivity growth will spread across European sectors

AI has a tangible, physical impact on transportation, bringing fully autonomous driving of trucks and cars closer to everyday reality. However, given legal concerns and restrictions, this will continue to be a gradual process through the development and expansion of driver assistance systems.

In logistics services and supply chain planning, where AI has already come a long way, more advanced applications could likely add the most near-term value. The world is an increasingly complex and uncertain place for international shippers and their logistics partners to operate. That makes the game of matching supply and demand (preferences) more difficult. Over the past few years, the reliability of international shipments has weakened due to the shocks of the pandemic, wars and geopolitical tensions. More extreme weather also brings with it ongoing uncertainty. All of this leads to fluctuations in supply and demand, with seasonal patterns changing, while sustainability policies are also having an increasing impact. As a result, shippers and their logistics partners are looking to build resilience by diversifying or securing larger buffer stocks to reduce risk. But more intelligent and predictive analytics could likely also be part of the answer.

There is still much room to improve decision-making by taking into account more variables and (large amounts of) data, such as traffic and waiting times, weather conditions and environmental footprint. This could allow players to improve transportation forecasting, find better alternatives for customers, enhance reporting, and save on equipment and staff rentals. Logistics is a cost-driven, low-margin business. When it comes to improving efficiency, the potential gains mainly focus on cost reduction, and here too AI can make a difference. Optimizing route planning and load factors still offers potential benefits. For example, in European road transport, progress in reducing empty journeys has stalled over the last few years, with 20% of truck journeys still made on empty routes.

This sounds promising, and companies can incorporate internal and external data. However, it is worth realizing that cooperation in the supply chain and data exchange are critical factors. Therefore, mutual interests should be in the foreground here. In particular, road transport is still largely the domain of small and medium-sized enterprises (SMEs). They are sometimes able to leverage the services of their charterers, but unlocking the potential of AI requires both ICT investment and expertise, where scale is necessary.