AI is capturing logistics expertise faster than most companies realize. Here is what port drayage carriers and shippers should understand about the shift.

Artificial intelligence tools have moved from novelty to daily infrastructure across the transportation and logistics industry. Route optimization, dispatch automation, load matching, predictive maintenance, and documentation workflows are all areas where AI is now embedded in how freight moves. Most carriers and shippers view this as straightforward productivity progress. But a deeper question is starting to surface: when AI learns from your team, who actually owns what it learned?

A recent Wall Street Journal piece raised this question in the context of corporate workplaces, and the answer it arrived at applies just as directly to the port drayage and trucking world. The expertise your team builds over years of working a terminal, managing chassis shortages, anticipating demurrage windows, and solving problems that never appear in a manual is being absorbed by the platforms you use. And in many cases, it is becoming the platform’s asset, not yours.

The Expertise Problem in Port Logistics

In drayage, institutional knowledge is a real competitive advantage. Knowing when Norfolk International Terminal gate queues back up, which chassis pools run short after a large vessel call, how to sequence container pulls to avoid detention, or which contacts to call when a container goes on hold are not skills you find in a textbook. They are built through experience, relationships, and years of working the Port of Virginia.

When that knowledge gets entered into an AI-assisted dispatch system, a load management platform, or a customer communication tool, the system records it. It learns from the patterns your team creates. The prompts, the decisions, the workarounds, and the successful approaches all feed back into the platform’s model. Over time, the system becomes more capable, not because it was programmed with your expertise, but because your team taught it.

This is useful in the short term. But as the WSJ piece points out, it raises a legitimate long-term question for anyone whose value is tied to what they know.

What This Means for Carriers

For trucking companies and drayage carriers, the practical implications fall into two areas.

The first is workforce. Experienced drivers and dispatchers carry terminal-specific knowledge that takes years to develop. When AI tools absorb that knowledge through daily use, the value of an individual’s expertise within the organization shifts. The system can surface answers that once required a phone call to the right person. That is efficient, but it changes the relationship between experienced employees and the companies that employ them. Carriers who are building a culture of retention need to think carefully about how they are capturing and deploying institutional knowledge, and whether their team understands what is happening.

The second is vendor dependency. If your routing decisions, dispatch logic, and customer communication patterns are all being learned by a third-party platform, the cost of switching that platform rises over time. The tool knows how your operation works. Walking away from it means starting over on the learning curve your team already paid to build. This is worth considering when evaluating technology contracts and long-term platform commitments.

What This Means for Shippers and 3PLs

For shippers, BCOs, and third-party logistics providers (3PLs) managing freight through the Port of Virginia, the question is slightly different but equally relevant. When you work with a carrier who uses AI-assisted tools for scheduling, tracking, and communication, the patterns of your freight, your preferences, your exceptions, and your escalation behaviors are all potentially being learned by that system.

That is not inherently a problem. Better pattern recognition can mean better service. But it is worth understanding what data your carriers are capturing about your freight operations, how it is being used, and whether it is contributing to a platform that benefits your operation specifically or a general model that benefits the platform’s entire customer base.

The Human Expertise That AI Cannot Absorb

There is a boundary to what AI platforms can learn from transactional data, and it matters for how carriers and shippers should think about their teams.

Relationship-based problem solving at the Port of Virginia does not fully translate into system data. Knowing the right contact to call at Virginia International Gateway when a container is misdirected, understanding the informal communication that happens between terminal staff and experienced drivers, or being trusted enough to get a situation prioritized during a congested vessel call period are capabilities that come from human relationships built over time. They generate outcomes in the real world, but they do not generate data inputs that a platform can learn from in any meaningful way.

This is one reason Century Express Virginia has placed consistent emphasis on driver retention and team continuity since 2007. The relationships our team has built at NIT, VIG, and throughout the Port of Virginia community are not replicated by any software tool. They are the product of years of showing up, doing the work, and building trust with the people who operate the terminals. Our port drayage capability is built on that foundation, and so is everything we offer in rail drayage, refrigerated drayage, hazmat drayage, and specialized freight.

A Practical Note on AI Adoption in Logistics

AI tools are worth using. The efficiency gains in dispatch coordination, documentation management, and predictive maintenance are real, and carriers who ignore them will fall behind. The point is not to avoid the technology. It is to adopt it with clear eyes about what is being exchanged.

Your team’s expertise is a meaningful input into any AI system you use. Treating that input as valuable, understanding what happens to it contractually, and ensuring your workforce understands the dynamic are reasonable steps for any carrier or logistics operation to take before signing long-term platform agreements.

For shippers and 3PLs evaluating carriers, asking how your freight data will be used and whether your operational patterns will be shared or siloed within a platform is a fair question during the procurement process.

The logistics industry is moving fast on AI adoption, and the Port of Virginia market is no exception. Century Express Virginia will continue tracking how these tools affect port operations, carrier relationships, and the workforce that keeps freight moving through Hampton Roads. If you have questions about how we operate or want to discuss your freight needs, contact our team at (757) 494-9200 or visit our contact page.