Fontana: When it comes to AI, there is no one-size-fits-all solution

AI adoption looks different for every fleet, making operational priorities, human judgment, and ongoing adjustments key to success.

Key takeaways

  • AI strategies should reflect each fleet’s operating conditions, equipment, and business goals.
  • AI can automate tasks and identify data patterns, but human oversight remains essential.
  • Fleets can improve the value of AI by adjusting its use to meet their specific operational needs.

Throughout my life, I have found that very few things that have the label “one size fits all” actually fit all sizes.

The same is true for AI; there is no one right way to use it in your operation. However, I do believe that there are some things that you can do incorrectly. One is to completely ignore AI, and the other is to think it’s the solution to all of your problems.

AI can be a powerful tool, but it is just a tool, and as with any tool, it must be used properly. AI is good at automating tasks and processing large amounts of data. It can be useful for writing first drafts of marketing materials, but as with any first draft, a first draft from AI needs to be edited and polished by someone on your staff. While AI can find patterns and trends, you can’t rely on it to tell you why those patterns are occurring.

Essentially, there are things AI can do and things it cannot, and those things could be different depending on the nature of your business.

There is an old saying when trying to explain fleets to someone new to trucking: “When you’ve met one fleet, you’ve met one fleet.” While there are similarities between fleets, the reality is that each one is unique because there are so many factors that play into how the fleet is operated.

Some fleets keep their trucks for seven years, while others trade them after two; some lease trucks, while others purchase them outright. Some operate only sleeper tractors, while others operate a mix of sleepers and day cabs, and still others operate only day cabs.

There are fleets operating in the mountains of the western U.S., others on the flat Great Plains, others still in dense urban areas, and some whose drivers traverse a variety of terrain types.

Some trucks weigh out, while others cube out. Some only leave the terminal partially full. Some fleets pull reefers, while others pull 53 ft. dry vans, and still others operate flatbeds. Some fleets run only diesel-powered trucks, others dip their toes into alternative fuels, and still others are all-in on zero-emission goods movement.

You get the idea.

In addition to operating differently, each fleet has its own set of core operating principles. And while there are likely some similar principles on the list, the priority placed on those principles can be different.

All of this plays into decisions about using AI. While I can tell you how we use AI here at Transervice, the areas in which it is most beneficial may differ from yours.

And as we delve into our use of AI, we continue to make adjustments so that it learns more about us and can be of greater value to our operation.

I encourage fleets to consider how AI can help their operations. It is important to keep in mind that an AI solution must be tailored to specific operating conditions, as well as your fleet's mission and vision. When it comes to AI, there truly is no one-size-fits-all solution

About the Author

Gino Fontana

Gino Fontana

Chief operating officer and executive vice president at Transervice Logistics Inc.

Gino Fontana, CTP, is COO and EVP at Transervice Logistics Inc. His operational expertise emphasizes cost savings, process efficiency and improvement, superior quality, and people management skills. He has more than 35 years of experience in the transportation and logistics industry with both operational and sales experience.

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