This article was written by Asparuh Koev, CEO of Transmetrics
When C.H. Robinson’s stock dropped sharply in February after a smaller AI-powered platform claimed it could help shippers move far more freight without adding staff, CEO Dave Bozeman’s response was, more or less, don’t worry, scale and size always win. He told Reuters that C.H. Robinson’s size and vast proprietary data give them a competitive advantage instead of posing a threat, while also claiming that smaller brokers would struggle to keep up, fuelling further industry consolidation.
But this is not entirely accurate. Although size has historically been a stand-in for competitive advantage in freight brokerage, it has never been the pure advantage itself. The real determining factor for companies that win and those that don’t is how a firm uses AI.
In the U.S. context, Bozeman’s argument has more standing. American trucking companies operate in one huge market, with one currency, one regulatory system, and one dominant language. Scale builds more smoothly against that backdrop; the more freight a broker handles, the more data it gathers, and the better its AI gets at predicting prices and matching loads. Size is indeed closely connected to advantage in that environment.
Europe is completely different. One shipment can easily pass through four countries, which means four markets, four currencies, four languages, and four regulatory systems. That fragmentation trickles down to documentation and compliance requirements, the very details that complicate operations. A broker operating in Europe has to navigate all of these factors across hundreds of shipments.
How AI Has Changed The Fundamentals of Freight Brokerage
Understanding why integration depth and orchestration matter, particularly in Europe, means looking at what AI impacts in freight brokerage on a daily basis.
Perhaps the most prominent impact felt is in load matching. Traditionally, freight brokers would match available trucks with freight by making lots of phone calls and sending out messages, and leaning on existing relationships and experience. Manually done, this process would often present plenty of bottlenecks and quickly descend into chaos with one minor error.
AI can process thousands of data points and variables all at once, including individual carrier reliability and performance, trucks’ current locations, delivery times, route efficiency, costs, and more—presenting the best matches in a matter of seconds.
The second area transformed by AI is pricing accuracy. AI tools help remove the guesswork, pricing dynamically based on real-time supply and demand, seasonal patterns, fuel costs, and route-specific history. It is particularly valuable for brokers operating across multiple countries and markets, as European firms do, as AI helps ensure consistent accuracy.
Finally, freight brokers, shippers, and anyone working in logistics and transportation want predictable and reliable services. Delayed cargo or a blocked route can cause cascading consequences across the supply chain. AI tools that forecast delays, flag capacity crunches before they happen, and route around known trouble spots allow brokers to make service commitments. That reliability becomes a commercial advantage since shippers pay premiums for brokers they can actually count on.
When considering the sheer breadth of operations that freight brokerage and logistics span, these wins cannot be dismissed as small efficiency gains. AI’s presence is redefining the very quality, as well as the speed, underpinning decision-making. Ultimately, treating AI as a feature and not a foundational element leaves freight brokers with very limited, short-term wins.
What Defines A Durable Winner
Plenty of freight brokerages now use AI, but that does not mean every firm is using it to build durable advantages and maximally resilient operations. The industry’s divide is not between companies with AI and those without, but between the ones embedding AI at the core of decisions and those treating it as an isolated add-on.
While AI can be used to accelerate one task in 83% of transportation occupations and is widely adopted in trucking, tools have largely been confined to specific tasks. For example, a dashboard to show optimized trucking routes or a customer care bot to answer simple questions. AI, however, is not integrated into workflows or orchestrated as an underpinning layer to every operational decision. A dispatcher still matches loads largely the way they always did, and AI then produces a report they quickly glance at afterward.
This approach to AI might make short-term progress, but that perceived growth will stagnate. Why? Because the underlying decisions themselves have not changed. Moreover, this piecemeal approach to AI deployment only magnifies silos in an already fragmented setting for European operators.
Winners with durable advantages take a different approach, building their data pipelines and orchestrating tools so that pricing, load matching, and network planning all run through AI rather than alongside it. Instead of a dispatcher skimming through an AI-generated report or dashboard, they’re acting on a recommendation that has already factored in real-time capacity, historical service reliability, and current market pricing.
This is where agility comes in, and size is no longer a sure indicator of success or competitive advantage. A leading freight broker with vast datasets but treats AI as a siderunner will still be making slower, less accurate, and less informed decisions than a smaller counterpart that’s rebuilt its workflows around AI from the ground up.
Consolidation in freight brokerage will probably still happen, but the companies that survive and grow won’t do so purely because of how large they are. The long-standing winners will be the firms that are making better decisions fast, thanks to embedded AI as a foundational element across operations. The real race is not out-scaling the competition, but about integrating smarter and more strategically to embed AI deeper into the areas driving the most impact. In Europe, especially, where scale was never a clean advantage to begin with, that race is already underway.
Asparuh Koev is the CEO of Transmetrics, a Bulgarian scaleup that helps improve efficiency and profitability for logistics and trucking companies.
Asparuh has worked in the transport and logistics sector for more than two decades. Over the years, he has established several companies, including Sciant, an engineering services company later acquired by VMware and IntelliCo Solutions, which delivers IT digitization for the transport industry. Koev co-founded Transmetrics in 2013 and, as CEO, he combines IT and domain expertise to grow a company that is bringing truly cutting-edge technologies to the sector.
Featured image: Bernd Dittrich via Unsplash+
Disclosure: This article mentions a client of an Espacio portfolio company.
