Ozinga

James Kornas began his career in manufacturing engineering at General Motors before transitioning to the rail industry in 2006 with Norfolk Southern. Over the next two decades, he advanced through leadership roles, joining the executive team at Patriot Rail, where he expanded the company’s short-line portfolio through organic growth and targeted acquisitions.

As Executive Vice President of Rail at Ozinga, Kornas leads the strategic integration and optimization of the company’s rail assets, building on a 97-year legacy. Since joining in 2024, he has brought a commercially driven, operationally rigorous approach, overseeing two short-line railroads and a national logistics network. He aligns rail infrastructure strategy with Ozinga’s goals in concrete, cement and aggregates, ensuring rail remains a key competitive advantage and driver of growth.

As a Purdue University graduate with a B.S. in Industrial Management and Industrial Engineering, Kornas is known for leveraging rail-driven innovation to create competitive advantages, focusing on sustainable expansion, and maximizing asset value across every mile.

Through this interview, Kornas highlights the need for the rail industry to move beyond outdated tracking systems, advocating for smarter asset management through AI and telematics. He stresses the importance of industry collaboration to standardize technology and enhance rail’s competitiveness in a changing logistics landscape.

Overcoming Archaic Challenges: Transforming Rail Asset Management

For much of its history, the rail industry has viewed railcars as simple vessels—tools for moving goods from origin to destination and back, with little attention paid to how they were tracked along the way. While this mindset was once adequate, it has become increasingly out of step with the demands of modern supply chains.

We’re laying the groundwork for intelligent decision-making by funneling all the GPS, telematics and software-derived data into a central repository.

Until recently, the tracking technology underpinning rail logistics hadn’t changed much in decades. In the 1970s, railcar monitoring meant affixing a basic barcode, an Automated Car Identification (ACI) label, to the side of each car. That evolved into the Automatic Equipment Identification (AEI) RFID tag used today—in essence, the process remained passive and imprecise. These traditional tools are no longer sufficient for Ozinga, which manages a fleet of more than 650 railcars. So, we see a different path forward—that is grounded in visibility, precision and performance.

We transport specialty commodities and serve customers with precise, time-sensitive expectations. To meet those demands, we need clarity—knowing exactly where our assets are, what they’re carrying and how they’re moving through the system. And yet, we’ve been limited to static, outdated methods that don’t give us real-time visibility into critical movements. That lack of insight has made it increasingly difficult to fully optimize our railcar fleet, manage inventory and maintain production efficiency.

Recognizing this, we’ve taken a proactive step toward change. Rather than accepting the limitations of the status quo, we’ve begun implementing a proprietary visibility solution on a select subset of our fleet—designed specifically to align with the operational and commercial needs of our business. This is our approach to smarter railcar tracking, built around the way Ozinga operates, with the flexibility to evolve as our fleet grows organically and inorganically.

We’re not waiting for change. We’re building the blueprint for what modern rail asset management should be.

The Path Ahead: Smarter Railcar Management with AI and Telematics

In the past five to seven years, I’ve seen the rail industry begin to embrace a future that other sectors adopted long ago. With advancements in telematics, GPS and artificial intelligence, we’re finally witnessing a fundamental shift—a shared recognition that the approaches that brought us here are no longer sufficient to take us forward.

Across the board, new third-party providers are offering GPS and telematics-enabled modules—solar-powered, battery-backed hardware that allows continuous tracking of railcars across the North American network. For a railcar owner and operator like me, that’s a game-changer. I no longer have to rely solely on the railroad’s internal data. I can now validate, cross-reference and take back control of our fleet.

But where it truly gets exciting is when we layer in AI. For me, 2025 marks a turning point—we’re not just collecting location data anymore. We’re laying the groundwork for intelligent decision-making by funneling all the GPS, telematics and software-derived data into a central repository. This integrated system allows AI to analyze complex patterns, from small details—like the exact time a rail car is released— to broader trends. For example, it can spot that a car leaving Chicago at 2 p.m. takes four hours longer to reach Dallas than one that leaves in the morning. These insights can help reshape entire logistics networks.

By processing these rich datasets, AI can not only optimize individual rail moves but also inform strategic decisions that improve railcar usage and infrastructure performance at a macro level.

If the entire rail ecosystem began to apply AI to movement patterns, dwell times or yard delays, we could transform this fragmented network into a more synchronized one—unlocking capacity, reducing friction and finding new efficiencies that simply weren’t possible before.

Unifying the Railcar Industry: A Path to Collective Progress

The most important step we in the rail industry can take right now is to break down silos. Railcar owners, lessors, suppliers, shippers and railroads all need to come together and treat technology as a shared solution—not as a point of contention passed between parties.

This was a central theme of my presentation at the Midwest Association of Rail Shippers earlier this year. Since the mid-2000s, the industry has experienced a steady decline in general merchandise freight volumes, consistently losing ground to more agile alternatives—particularly trucking. This decline has not stemmed from a lack of capability, but from a hesitancy to evolve. Ongoing inefficiencies, operational friction for shippers and a reluctance to modernize have steadily diminished the industry's role within the broader logistics ecosystem.

We must be clear-eyed about rail’s distinct strengths and limitations. Rail will never mirror the flexibility of trucking—and it should not attempt to. Its power lies in long-haul efficiency, environmental sustainability and economies of scale. The future competitiveness of rail depends on leaning into these advantages while incorporating modern best practices and pioneering technology that supports precision and network fluidity.

Technology gives us a real opportunity—not just to slow the decline, but to redefine the future of rail. But it’s not going to happen by chance. It’s going to take real collaboration, shared vision and a willingness to look at our challenges through a new lens. This is a team sport. So, if we’re serious about competing in the modern logistics landscape, we have to stop working in isolation and start moving forward as one.