AI in trucking: Common questions answered

Estimated reading time: 4 minutes

Artificial intelligence (AI) is currently one of the most talked about topics in trucking. The ability for technology to effectively perform tasks that have traditionally required a person to intervene drives imaginations and raises questions about what the future could look like.

Below, I’ll be answering common questions about AI in truck driving and giving some insights into how it’s improving the truck driver experience.

Disclaimer: The perspectives shared in this blog have been shaped by both my experiences and my opinions, and everyone and every company has their own point of view of how AI is impacting the industry.

Key takeaways

• Generative AI can impact the driver experience through faster problem resolution, more natural communication and fewer repetitive processes.
• Schneider is using an AI-enabled agent to handle basic requests from drivers, which has led to faster response times and fewer follow-ups.  My view is this just the tip of the iceberg in terms of opportunity.
• Everyone should have three things in mind about AI: it has already been a critical enabler of our modern day to day for years and there are many forms of AI.  The latest hype being around Generative AI (GenAI) we should approach it with optimism as well as an appropriate amount of reserved skepticism and we should view GenAI as a copilot, not the pilot – critical thinking is likely still required.
• Companies have a responsibility to make sure AI tools are doing the right thing before they're deployed at scale.

How can AI make a truck driver's job easier?

While AI itself is not new to trucking, what is new is how fast it's evolving, and how much it is impacting drivers’ day-to-day experiences. One of the biggest, most recent developments is the widespread adoption of generative AI.  

Think of generative AI as a Swiss Army knife. Old-style chatbots followed a rigid script: if you said this, it did that. If your situation didn't match the flow, you’d hit a wall. Generative AI doesn't work that way. It can reason through your situation, pull from multiple sources and respond in a way that fits what you need.

You may be more familiar with generative AI than you realize. If you’ve ever used applications like ChatGPT, Google Gemini or Microsoft Copilot, you’ve used generative AI.

Why does this matter to drivers, though? Here are some ways generative AI is improving the driver experience:  

• Faster issue resolution: AI-assisted support tools can understand the context of a driver’s situation, gather relevant information and either resolve the issue directly or hand it off to a human team member along with the already-captured details.
• More natural communication: The experience of interacting with AI-powered tools has improved dramatically. It no longer feels like arguing with a phone menu. Voice capability has reached a point where a phone call feels like a real, two-way conversation.
• Fewer repetitive processes: Anything that used to require back-and-forth to gather basic information can now be handled faster, freeing up time for the work that requires human judgment. The more information it has about the problem, to more likely it can accurately help solve the problem.

The bottom line is this: AI handles transactional work so people can focus on meaningful work.

What AI tools are truck drivers already using?

At Schneider, drivers have been interacting with AI for years through tools built into their work. Some of examples of this include:

• Refining load assignments from millions of possible route combinations to match drivers with loads to maximize productivity and meet driver preferences, leading to more home time and earning potential.
• Automating Estimated Time of Arrival (ETA) updates to improve customer visibility and create a more seamless delivery process.
• Helping enhance drivers’ skills and reaction time through driver-assist technology.

Most recently, Schneider implemented an AI-enabled agent designed to support drivers by interpreting their requests for information and responding with accuracy and speed.  

How does it work? Simply put, basic requests that might sit in a queue (like finding billing information and customer reference numbers) are handled by the AI-enabled agent. The agent is semi-autonomous, meaning it will respond on its own. If it hits a situation outside its training, it doesn’t guess. It pauses and transfers that case to a human.    

The goal isn't to replace the person helping drivers. The goal is to instantly provide answers when it can, and if it can’t, skip the information-gathering phase entirely so the team-member already knows the situation and can focus on solving the problem instead of asking the driver to repeat the details.

For drivers, this leads to:

• Immediate responses (no phone queues)
• Faster resolution of common issues
• Fewer follow-ups and handoffs

Ultimately, this all means drivers spend more time moving and less time waiting. At Schneider, drivers are already feeling the positive impact of this change. According to Lemine, a Schneider intermodal driver, the speed of AI-powered responses has been noticeable from day one:

“The first interaction I had with the agent was when I was delivering a container. I sent a message requesting a reservation number. The response time after my initial request was about 7 to 8 minutes.”  

What should every truck driver know about AI?

First: Drivers have already been experiencing AI for years. Navigation, freight matching, optimization — that's AI. Generative AI is just the next layer. It's more personal, more conversational and more capable.

Second: Approach AI with optimism. There's so much opportunity with this technology, so take advantage of it. Be smart and remember to protect your data, but don’t be afraid to embrace it.

The pace of improvement in the last few years has been unlike anything I've seen in this industry. If something doesn't work well today, just give it time. Every time we’ve seemingly hit a roadblock and thought “this is as good as it’s going to get,” the technical challenges have been overcome.

Third: Remember that AI is a copilot. AI can assist, but you still make the decisions. This isn’t a limitation, but rather how it's designed to work. Your experience and judgment are still the most important part of the process. AI just handles more of the noise, so you can focus on what matters.

What could AI in trucking look like in the near future?

For drivers specifically, I expect the biggest changes to come in two areas.

The first is proactive problem-solving. Right now, most AI tools are focused on resolving issues after they come up. The next step is working upstream and catching problems before a driver even opens a ticket. The best interaction, in this case, is the one that never has to happen.

The second is knowledge on demand. There's an enormous amount of information available to support drivers — policies, procedures, answers to common questions — and a lot of it isn't easy to find quickly. AI tools in development are designed to surface that information exactly when it's relevant, in plain language, without requiring a driver to dig through documents or wait on hold.

What are the biggest barriers to AI adoption in trucking?

The technology itself is not the biggest challenge. Most people already use cutting-edge tools in their everyday lives – like ChatGPT or Google Gemini – to search for information or get help with a task.  

The challenge in a company setting is that the stakes are higher. When you're using an AI tool personally and it gives you a bad recommendation, you catch it and move on. In an enterprise environment, if someone doesn't catch a mistake, or if the AI is making decisions that affect a driver's experience, pay, or load, the consequences are more significant.  

That's why adoption in trucking moves carefully. Not slowly by any means, but deliberately. There's a responsibility to make sure AI tools are doing the right thing before they're deployed at scale.