Omnitracs' Road Ahead blog

Improving driver retention with artificial intelligence & machine learning

Emilie Worsham
Business Systems Analyst

It’s no secret that technology has had a significant impact on the transportation industry in recent years, transforming a variety of processes, from how drivers operate on the roadways to how fleets manage their back offices. Two technologies that have had a profound impact on the industry lately are artificial intelligence and machine learning.

Defined as automated solutions with the ability to harness data in real time and adjust accordingly, artificial intelligence & machine learning leverage algorithms to perform specific day-to-day tasks without defined instructions – making operations significantly smarter and more productive.

With the power to streamline processes, eliminate financial burdens, and enhance driver safety, artificial intelligence & machine learning have the potential to revolutionize the business of transportation entirely. Keep reading to see how your fleet can leverage these emerging technologies to retain drivers and increase revenue.

The importance of driver retention

Competition for qualified drivers is at an all-time high, as the industry continues to work to fill the need for close to 60,000 operators. Paired with the fact that the cost to hire and train new employees is exponentially more expensive than retaining current drivers, it’s critical that fleets do what they can to maintain their current workforce and reduce the industry-wide turnover rates, which reached 78 percent at the end of 2018.

How artificial intelligence & machine learning can help

To stay competitive and maintain a productive workforce, fleets are always working to understand and meet the needs of their drivers. However, with distributed workforces and the challenge of collecting individual driver preferences, gaining that understanding has been a difficult task.

Today, fleet managers and human resource teams can apply artificial intelligence & machine learning technologies to the timely data already being collected by electronic logging devices, in-cab videos, telematics systems, and more. By analyzing data such as driver tenure, shift difficulty, family structure, time away from home, and salary, artificial intelligence & machine learning technologies can:

  • Alert fleets of any unhappy or at-risk drivers so managers or human resources teams can speak with drivers directly and proactively resolve any possible reasons for leaving.
  • Determine unmet employee needs and preferences across a company so fleets can more accurately pinpoint areas to address, such as reviewing current salary levels or altering schedules so drivers can spend more time at home.


Discover how you can apply artificial intelligence and machine learning to your data and retain your drivers at


This is part one of a three-part series:

Improving driver retention with artificial intelligence & machine learning

Improving driver safety with artificial intelligence and machine learning

Reducing driver fatigue with artificial intelligence and machine learning