In a recent webinar on Driving Success, DQM Connect tackled the issue of artificial intelligence (AI) in trucking.
This particular webinar specifically touched trucking compliance technology, looking in detail how fleets are using automation and AI — and why it’s critical to understand the difference between the two.
DQM’s Emily Buchanan and Leanne Hill shared real-world examples, practical advice, and lessons learned from conversations with fleets across the country.
AI vs. Automation: What’s the Difference?
The two terms can be a bit confusing. Hill put the differences into perspective early in her remarks.
“So automation is like a fixed process,” Hill said. “It’s repetitive and it’s rule-based. Whereas AI is moreso driven by data. It needs data in order to train itself in, in order to improve on itself.”
Hill gave an example of automation beig like auto filling forms or automatic notifications sent to drivers for renewals. AI, by contrast, uses data to detect patterns. It powers tools like in-cab driver monitoring and auto-summarizing email content. Both are forms of trucking compliance technology, but they solve different problems.
“For instance, chatbots that you see on a website that can answer repetitive or frequently asked questions,” Hill cited that’s an example of AI as well as, you know, in our industry, flagging risky or repetitive behavior from ELD data, that’s an example of AI as well. So those are kind of the differences. Automation and AI are kind of one and the same — but they’re different.”
Where Fleets Run Into Trouble
One common pitfall is using AI tools for employment verifications. These tools can check massive databases quickly—but when they don’t return results, fleets assume they’ve “done their due diligence.”
The truth? FMCSA expects three meaningful attempts to verify past employment. Instant pings don’t count. This is a clear case where trucking compliance technology can mislead if not understood correctly.
AI is improving, but it is not perfect.
Systems miss license suspensions, overlook warning signs, or reject good candidates because of flawed logic. No matter how advanced your software, both Buchanan and Hill agreed that human review is still required.
Regulations (like Title 49) are clear: every driver file must be reviewed by a person. Trucking compliance technology should support your team, not replace it.
One of the common uses of AI today in trucking is in cameras, a subject that Lee briefly broached.
“The systems are trained to detect behaviors like distracted or fatigued driving,” Hill said. “And when risky behavior is identified, AI can trigger those alerts to the safety team, allowing them to take proactive steps to prevent accidents and reduce liability in the future. So that was kind of a lot. But with all that being said, in my humble opinion, the AI tools at hand, at least for the transportation industry, are not at the level where we should put our full trust in it because it’s still gonna make mistakes and it’s still gonna need human oversight in order to catch those mistakes.”
As tech evolves, the FMCSA may update its rules. But for now, the line between convenience and compliance must be respected.
“I think it’s gonna be interesting in the future of what is compliance versus convenience and don’t allow convenience to move away from the ultimate goal, which is safety and compliance,” Buchanan said.
The overall consensus was the use of AI should be to enhance decision-making, not to replace it.
Bruce Guthrie is an award-winning journalist who has lived in three states including Arkansas, Missouri and Georgia. During his nearly 20-year career, Bruce has served as managing editor and sports editor for numerous publications. He and his wife, Dana, who is also a journalist, are based in Carrollton, Georgia.
