Artificial intelligence is already changing how transportation companies plan routes, manage freight, and serve customers - but most organizations are still in the early stages of figuring out what that means in practice. New survey data and a panel discussion hosted by Transporeon, featuring leaders from Bekaert, FERCAM, Hegelmann Express, S2data, and Trimble, offered a realistic look at where the industry stands and what comes next.
The Pulse Report 2026, based on responses from more than 230 shippers, carriers, and logistics service providers across Europe and North America, found that 66% of respondents expect Agentic AI to reduce manual work, with cost savings and faster decision-making close behind. Those expectations are already translating into real operational changes, though adoption varies widely across organizations.
AI is moving from pilot to practice
The panelists agreed that AI is reshaping transportation management today, but they also acknowledged that many companies are still taking what Lucia Danisova from Bekaert called "baby steps." Carlo Pinamonti from FERCAM described the practical value in concrete terms: "Our customers expect speed, transparency and flexibility. Using AI together with more than 80 years of transportation experience allows us to respond quickly to market demands and make smart operational decisions."
Denys Kochurin from Hegelmann Express argued that the shift is already underway and will accelerate. What separates the organizations making real progress, said Bernhard Schmaldienst from Trimble, is treating AI as a business transformation initiative rather than a technology implementation. Success depends on data quality, solving tangible business problems, and getting stakeholder buy-in - not on the sophistication of the algorithms.
Schmaldienst captured the tension well: "AI is both overhyped and underestimated." Some organizations expect too much too soon; others underestimate how deeply it may reshape transportation management over the next five years.
Connected data is the bottleneck
Transportation depends on information flowing across shippers, carriers, logistics providers, customers, and technology platforms. Much of that information remains trapped in disconnected systems - and that is the biggest barrier to realizing AI's potential, according to Stefan Kremsner from S2data.
"The more information we have, the better we can plan," Kremsner said. "The more information is available for the AI to make decisions, the better they can be." Connecting data across ERP, TMS, warehouse, production, and partner systems allows AI to support smarter planning decisions and optimize operations across the broader network. For managers building these connections, structured training can help bridge the gap between understanding AI's potential and applying it to daily operations - an AI Learning Path for Transportation Managers offers a practical starting point.
The shift also changes what transportation professionals do day to day. Less time spent on manual data entry and reactive firefighting means more time for exception handling, customer relationship management, and strategic planning. Those shifts in operational focus are part of why AI for Operations training has become relevant beyond just the technology teams.
Why this matters for managers
For transportation and logistics managers, the practical takeaway is straightforward: AI adoption is not a future scenario but a current competitive factor. The organizations gaining ground are not waiting for perfect data or complete clarity on every use case. They are connecting their systems, picking specific operational problems to solve, and building internal support one project at a time. Managers who start those conversations now - focusing on data quality and concrete pain points rather than abstract AI strategy - will be better positioned than those who wait for the technology to mature further. The full webinar discussion, including practical use cases and governance considerations, is available on Transporeon's blog.
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