How can commercial fleets benefit from AI?

0:00 Fleets have diverse missions and requirements

Today in The Garage, we’re recording live at ACT Expo 2026 in Las Vegas, Nevada. Around the show floor, there’s an incredible diversity of commercial vehicles of all types, from heavy tractors, trailers, buses, lots of electric charging equipments, specialty purpose vehicles of all kinds . And one of the things that we recognize is the importance of how technology can benefit fleets and benefit their different missions.

Whether it’s for preventative maintenance, ensuring uptime and reliability and safety, all the way through to autonomous trucking and optimized operations. Technology has a role to play in commercial vehicles and we’re beginning to see that. So many of the exhibits here are looking at how fleets are using technology in new ways to solve a diverse range of problems.

To dig into that topic, we have a special guest with us today. Our guest is Lawrence Bader, who spent thirty two years at UPS running and managing their fleet operations and now is an independent consultant. And Lawrence is going to share with us in today’s interview a wide range of problems that he encountered and fleets have to solve and how he’s seeing technology solving a range of those issues now and in the future. It’s a very interesting conversation on commercial vehicles.

Let’s go.

1:35 Introducing Lawrence Bader

Welcome to The Garage. I’m John Heinlein, Chief Marketing Officer with Sonatus. We’re here recording live at ACT Expo in Las Vegas 2026. I’m so well so excited to welcome Lawrence Bader to the podcast.

Lawrence, welcome to The Garage. Thank you, John. Appreciate it. We always have our guests begin by telling us about themselves and their background.

Please introduce yourself. Tell us about you.

Sure. Well, my name is Lawrence Bader. I recently retired from UPS after thirty two years.

Thirty two years.

That’s great.

Thirty two years is a long time, where I had the opportunity to run what we call global fleet systems.

And I spent my entire career in really the IT discipline, you will. But, you know, working for UPS gave me lots of opportunities to, to work in the airline space, to work in the the automated hubs. And in the last decade of my career, I actually focused on what we call ground transportation.

And that was basically the fleet of about 275,000 pieces of rolling equipment.

That’s a lot of that’s a lot of equipment.

That kind of insight is exactly what we’re looking for. We’re looking for to learn about you and what you what you learned from those that time. But begin first by telling us a fun fact about you as we always do on the podcast.

Well, you know, actually, John, I really enjoy building and racing cars. I didn’t start that really until later in life. As a matter of fact, I couldn’t even change a set of brakes until I was forty five years old.

But, you know, I was an an IT background for such a long time that when you build software, you don’t get your really hands on it. You don’t feel it and get you really overly overly experienced it. So, you know, I learned to to turn a wrench and, you know, be able to put that power to the ground, so to speak, and really just enjoy racing racing cars.

That’s that’s fantastic. I love that discipline. I must say it’s not an expertise I have, but I like building physical things. I do a little carpentry. I like to build stuff at home.

So Yeah.

I think that’s in touch with you what you build.

Right? Yeah. You see could see it tangible. I think it’s great. So now tell us about your what you do now and your company.

3:22 Transition to Consulting and Technology Adoption

Yeah. So, you know, after thirty two years of being in the industry, I didn’t really want to leave the industry just yet. So I made a lot of friends, and and you have to get a lot of opportunities here. So really, I’m just an independent consultant where I like to help fleets adopt technologies.

I had the luxury of really exercising a lot of products while I was at UPS. And if I can bring that to other fleets who don’t necessarily have the background or the time to kind of press into those things, you know, it’s just a good thing for me to do. But I also like to help, you know, vendors and solution providers who are developing products and, you know, help them to, you know, to determine really what’s gonna stick, what’s gonna sell to fleets. But really, all roads for me really lean towards autonomous vehicles.

You know, I’m trying to help accelerate the adoption of autonomous operations.

Fantastic. If someone wants to find you, what’s the name of your company?

Advanced Transportation Technology. Oh, great. And you could just find me on LinkedIn.

Okay. Well and we we’re happy to put a link in the show notes as well for people to be able to

find you.

4:16 Lessons Learned from UPS

So based on your long career at UPS, I’m wondering what are the lessons you learned there that can apply to fleets today that people can learn from?

You know, I think the biggest overarching learning that I’ve had throughout my entire career is you you really just gotta start. You know? You really have got to to to really move the needle by getting going. Oftentimes, we over-analyze solutions.

We often over-analyze where we wanna be, where what you wanna get accomplished. But start. Start small, gain some confidence, and then you can build on top of those, of of those wins, if you will. So it’s like iterative development is something in the IT industry we did a lot of.

And and if you don’t start, you’re never gonna get there.

4:54 Innovative Technology Solutions in Fleet Management

Can you share an example of how you see people using technology in a fresh and interesting way?

Yes. As as a matter of fact, something that I recently had the opportunity to to help deploy before I before I left UPS was, something we called keyless tractor. We actually physically removed the keys from the operation of a tractor.

No keys?

No keys. Yes. We actually, you know, did an encrypted digital key on the driver’s device, which allowed us to to issue electronic keys at the right time to the right driver for the right vehicle. So the the concept of having to manage keys or having the key board up there or keys in in coffee cans, we eliminated.

And that helped us in in numerous ways. Where one of them was, just driver time alone. The driver would, when they cut to came to the facility, they would go to the guard shack, and then they had to walk into the dispatch office. They would get assigned their tractor.

And sometimes the driver did not necessarily, want that particular tractor that was, scheduled for him. So he would maybe sweet talk to the person behind the counter to, give him a different tractor for the day. It just threw everything out of sorts, right? Here, now the driver can not have to walk through the dispatch office.

It’s automatically on their device. They walk through the unit. They can immediately open the doors when they get into range. It starts to pre-trip cycle, and off they go.

And like maintenance personnel, oftentimes, they couldn’t find the keys when they had to move the units to bring them into the shop. But now it’s actually on the device for the mechanic, and they can unlock the vehicle, move it into the place, and and begin their work without having to go to dispatch office.

I’m sure that allows you to provision keys and also revoke rights later when they’re not needed.

Yep. And that mean, that’s actually an interesting technology that could play in a lot of different spaces. Like, it’s with the rental market or the leasing market. But I think any fleet who has a key management problem, that’s just a just an interesting solution that’s out there. Right? Just just one of many.

Yeah. Just just using technology in a fresh way.

In a fresh way.

We’re finding and I think when we talk to customers, much times the perfect is the enemy of the good. Absolutely. And people are trying to arrange the perfect solution and what they end up with is nothing.

You’re never gonna get there.

It’s so much better to start with a solution that’s that works, that’s solid, and add to it. One of the things we’re our solutions provide is the ability to to change and iterate. You might begin using it for one application, and you realize, well, I have this other problem, but you can grow into that and you can expand.

Right. And I think we’re all discovering that today with def definitely with AI. You know, just collecting the data has been a tremendous amount of time we’ve all spent in in in in getting the data in our hands. But we didn’t know what to do with it. Right? We didn’t we couldn’t put action to it. So so now we can iterate on top of all the data we gathered over all those years.

7:25 The Role of AI in Fleet Operations

It’s a perfect transition because AI is such an important topic for us, an important topic we cover on the podcast now. So what are you seeing in AI as moving the needle today, and where do you see the opportunities, and where would you suggest people be investing in AI in the future? Because I think people think about AI and they immediately think about autonomous, which is important. I think they think about voice assistants and so on. But for me, that’s just the beginning of the scratching the surface of what’s possible. What do you see as opportunities?

Well, you know, to me, leveraging AI and leveraging all the data that you’ve collected is is really how can we begin to automate those mundane tasks? You know, let’s remove the human element out of the mundane tasks that are just simply repetitive. And then that’s just where we need to start. Right?

Well, you know, we we started back in our early days with with capturing telematics data, capturing GPS location. But, you know, that’s just the start of it. And and how can we take that data and get to true predictive analytics? How can we determine component failures before they occur?

How can we change our maintenance programs from away from, you know, time and miles based to really condition based, based upon, you know, what’s going on with the actual piece of equipment?

I think that’s such an important point you mentioned because when we think about maintenance today and we think about diagnostics, it’s relatively blunt instrument people are using. And it means that you’re probably doing excess maintenance you don’t need. Absolutely. And you’re doing it sometimes too late.

If we can use a better intelligence to both understand how the vehicle is actually being used instead of just as you say, the mileage schedule, and then look more specifically at at what your indications of problems are, I think that’s incredibly valuable.

Yeah. I think oftentimes, you know, the respectable fleets, those who need to deliver on time will will tend to over-maintain their equipment. And over to maintaining equipment’s expensive. Right?

I mean, you know, we would you know, as I’ve seen fleets out there who would actually replace tires before they’re they need to be replaced. They replace starters before they need to be replaced based upon just time and miles because they had to protect their reputation. Right. And, you know, if we can move towards this, actually look at the signals that are coming off, let’s just look at the electrical system as an example.

You know? You could absolutely change three or four major parts when you’re trying to trying to prevent a failure, whether it’s the battery or the cabling or the starter itself. Let’s actually go in and dig into the the signature patterns of the electrical circuit to see, you know, we can have AI actually predict, well, when is that starter actually going to fail?

You know, instead of replacing it every year, let’s replace it on an as needed basis.

Right. We’re we’re showing a demonstration just a few feet away from us in in the booth showing something similar to that, how you can use, you know, RP129 protocols to better understand the actual situation of the vehicle, help understand is it the starter or is it some is it a wiring issue? Is it some other issue? So instead of just brute force replacing things that aren’t broken, which gives you higher maintenance costs, higher downtime, You replace what’s broken when it needs to be

fixed

10:15 Michelin technology for tire monitoring

Now you mentioned tires as well. I think it’s an interesting application because, you know, tires are so crucial where the rubber meets the road literally. Right? Yeah.

But we have a collaboration with Michelin that we’ve shown recently using AI where they’re doing exactly what you said. They’re looking at specifically how the the vehicle is being used, how is the load varying over time, what’s the the weight, all those different things factoring in and and giving a better indication of how tires are actually wearing versus versus how they might be theoretically wearing. And that’s allowing the extended use of of tires for a longer time and again, less downtime and less unnecessary

maintenance. It’s using AI.

And we’re we feel that by putting some of the AI like that closer to the vehicle, you have the opportunity to do the kinds of calculations that you can’t do in the cloud. It’s too slow. It’s too far away. It requires too much data.

So that’s kind of the one of the visions we’re looking for.

Do you do you see that as viable?

11:10 Virtual sensors before and after production

Well, absolutely. I mean, what you can compute on the edge and and being able to get the processing done done away from the cloud, can you makes you, you know, far much more nimble. And also, you know, I’ve I’ve come across the the ideas, and maybe you guys have talked about this, with virtual sensors. You’re actually creating sensors from two or three other inputs and being able to gain deeper insight into that. I’ve actually seen that in a couple different locations.

It’s true. And one of the we’re showing some examples of of how that works in the past. We’ve got some collaborations with a vendor called COMPREDICT, for example, and others who are using virtual sensors to calculate things. Actually, there’s plenty of information to calculate a sensor result instead of putting in a physical sensor. And by doing that, they can avoid cost and simplify the vehicle. But what’s really exciting, and you and I were chatting about this, is imagine you realize that I wish I had a sensor after the vehicle was shipped and I have all the data, but darn I didn’t put the sensor in. You could put a virtual sensor in after production.

That’s that’s pretty cool.

And so it and one of the things we we chatted about is imagine a virtual hazard light. You realize that, well, when these combinations of situations happen, when I see this indication on this subsystem and that indication on that subsystem, it’s an indication that there’s going to be a problem coming soon. You could then raise a virtual hazard light that says, hey, look, you need to take this in for service, say, urgently, but that could be deployed as a kind of a virtual hazard light after

production

12:30 Diagnostics matters more when there is no driver

You know, I actually see that as we look forward down the road to autonomous trucking. When we have autonomous trucks running up and down our highways, which we will indeed have, you know, there’s not a driver in the seat. Right? And being able to detect an issue before it occurs, being able to articulate how far can I go with that autonomous vehicle?

Do I have to get off immediately at this next exit? Can I complete my mission? Or do I need to kind of plan my route to get to the next, you know, certified, repair facility that may be one hundred and twenty five miles away? I think that that’s an interesting play.

Yeah, so much of driver expertise, you know, we we respect drivers and their their their knowledge and their know how. You know, I think myself and and you and certainly professional drivers can see and feel that something’s not quite right.

Right. Absolutely.

And they want to adjust it. But as you go towards an autonomous world where the driver’s not driving or maybe not driving all the time, you might have a situation where you really need to be monitoring that in a new way.

Yes. Yep. And you have to mount it to both the tractor and the trailer. It’s true. You know, the trailer is also a very important aspect, which I’m now seeing more and more fleets adopt sensor technologies on those trailers.

Yes. Smart trailers is a big topic. And there’s nothing exclusive about any of these things we’re covering. I think they both apply to to the tractors and trailers both.

Yep. As I mentioned earlier, you know, encouraging fleets to just get started, and there’s a great example there. We’re just looking at TPMS or automatic tire inflation system on trailers. You know, they’re not everywhere right now, but, you know, the tires is one of the most important things.

And actually, I came across a fleet here recently who, who adopted tire pressure monitoring systems on their on their equipment, and they are now as they as you look at the roadside inspection data from, the states, they have zero tire violations.

And that’s phenomenal in our industry. And that’s just an example of where fleets actually picked up the ball, started simple, something that they knew knew about, and applied it. And now they’re being able to reap benefits from that financially, but also from a brand image.

14:22 Data Utilization in Fleet Management

So much of what we’re talking about relies on data. Think fleets have been collecting data for years, but a lot of that data I think has probably gone into a pile that’s never looked at. You know, what do you see as the opportunity from using data in smart ways to do some of these things we’re talking about?

Yeah. I mean, that that is an industry challenge. As I talk to a lot of fleets, there a lot of data is being collected, but it is collected in silos, and it’s too much data for any fleet to really put to action. So that’s really the key piece.

Now that we have AI, it’s gonna actually come in and create these, you know, these actionable insights. And we have to bring those actionable insights not to some email chain that goes out to everybody, not into a vendor dashboard where it’s buried only in in in certain vendors’ platforms. It needs to meet the operation where they are. Right.

Let’s roll that into their fleet management system or their work dispatch for the day or for the drivers, you know, the drivers panel inside the vehicle. Right. You gotta meet the operation where they are, not layer on another piece of technology, another screen, another portal that they have to log into.

That simply does not work.

Right. So it’s such a smart point because some of the data needs to go to the central fleet manager to understand perhaps collective maintenance…scheduling it. Some of it wants to go to the driver, but the answer is it’s both.

It’s not just, okay. If I just have an app for the driver, I’ve solved all the problems. Or if I just throw it into some, console a mile away. It needs to be a mixture of all of those things.

Well, and that’s a key piece here, which we really haven’t pressed into. But as I talked to a lot of fleets, their their challenge with adopting technology or AI in general is they’re very siloed. You know, it has to be in across the entire organization. The chief operating officer is the one who really needs to kinda get in and make sure that all of their business units are playing together, collaborating on bringing this technology into play. It’s gotta be the maintenance department, the dispatch department, health and safety, and, yes, the IT organization because the IT organization one that stitches it all together and makes it available.

Obviously, commercial fleets and commercial vehicles are different than, than passenger vehicles because downtime is is critical. Downtime is just money lost, directly money lost. So how do you see maintenance changing that? Do see the ability for us to do smarter maintenance, smarter predictive maintenance materially improving downtime?

Oh, absolutely. Yes. I mean, you know, today, we have to wait until it’s an after the fact. The failures already occurred.

It already throws the diagnostic trouble code, the DTC. We need to be in front of that, and we can actually pick up data from various sensors in a normal course of the operation, have a digital twin of that particular platform, and know when it has a deviation from that. So I can predict before the actual DTC code is ever thrown. That’s where the magic happens.

That’s where I can actually get in, pull the equipment off the road before it’s a breakdown on road. I can’t stand breakdown on roads.

Right. And now now that’s looking at an individual vehicle. I think the the opportunity, and you mentioned AI as well, is if we’re able to look at across a fleet, now we’re seeing patterns across a fleet that says, okay, I have this problem on this vehicle, but now I realize that it’s affecting other vehicles or other vehicles are going to have that problem soon.

Well, if they’re using the same components. Right? Or the same the the, you know, the the same tier one supplier has an issue across the different fleets. But, you know, even pressing into a specific make and model, we have issues with a specific make and model. And being able to take those earlier on before I continue to increase the number of of units that I bring on board, that that’s a gold mine.

So here at ACT, the the show is full of diverse vehicles of all kinds. There’s heavy construction. There’s buses. There’s there’s trucks. There’s trailers.. tractors, trailers. What are you some of the things that you see as interesting, here at the show, and what are you what are you focusing on looking at today?

17:53 Automation and Autonomous Vehicles

Well, for me, it is is getting back to automation. Alright? So a lot of companies are leaning into automation, putting that data to use, and then I’m taking automation a little bit further with autonomous vehicles, whether it’s over the road or on property shifting, especially in our class eight space. And so here at ACT, you do see a lot of the autonomous vehicle vendors here who are partnering up with some OEM suppliers here, and, I’m looking forward to seeing those on the road, and growing in numbers.

So when you think about autonomous, do you look at that as end to, you know, last mile autonomous?

Do you see it as primarily highway? How do you see the industry adopting this?

Well, I think the industry is gonna adopt, first of all, at the distribution centers or the hubs. So on-property shifting is what I’m referring to there. So moving the trailers around from a staging area to the dock door, pulling off the dock door, you know, outbound, and so on and so forth, and then over the road. So basically, you know, your long hauls, those that are going multiple states, you know, exceeding the the ELD hours of service rules, you know, going coast to coast. Right? A lot of times, we’ll put trailers on trains, and we’ll train them over the rail, which is not always reliable and timely. But if we can pull those off the road and put them in autonomous trucking and run for thirty two hours without refueling, that’ll be a great day.

I see. So it’s really kind of a mixture of from the the distribution center, which maybe people don’t think of as an important area. There’s lots of personnel-intensive work to move move things around there.

Oh, on the property? Yes.

Yeah.

And that because it’s an enclosed space, it gives you opportunities to do things differently than you could do on roads.

Yeah. It’s much more controlled. I don’t have to worry about public perception. Right? I can really, you know, manage how the yard behaves and operates. And to be quite honest with you, that’s a that’s a tough job. You know, if you’ve never ridden a terminal tractor or a shifter and you’re slamming into the back of that trailer loading that thing up, it’s it’s physically demanding.

To do it all day long, moving one after the other.

It’s not it’s not exactly a sought-after job. Right? People rather be on the road. Yes. Local.

And when you talk about over the road, you know, a lot of our drivers, they don’t wanna be gone for four or five days away from their family. So that’s just another great application that can really help the the livelihood of our drivers today.

So really looking for solving the right problems using different technologies because those may be different. Distribution center can avail itself of high resolution knowledge of the center, perhaps additional beacons and so on versus over the road has different issues, needs to have a broader highway map system and and so on like that.

Well, AI is certainly accelerating that, it’s been basically physics-based AI. Physics AI is what’s really, really, doubling down and accelerating the growth of autonomous and automated operations.

It’s an exciting future to think about all of those things working together. I think the the fleet management job is a is a hard job. You’ve seen that firsthand.

Absolutely.

But I think if you if you do it right, it can create incredible results from the industry.

20:38 Conclusion and Future Outlook

And, bottom line, you need to lean into technology. It’s there. It works. And if your company doesn’t lean into it, you know, you’re gonna be missing out a lot of opportunity and there’s gonna be other companies who are gonna surface and could potentially just, you know, simply run past you.

Well, Lawrence, we’ve had a wide ranging discussion and your experience in the industry is so valuable. I appreciate you coming by and spending time with us. My pleasure. Surely enjoyed it, John. If you like what you’re seeing in the this episode, please like and subscribe to see more like it, both here from ACT Expo and our other shows all around the world. Thanks for watching. We’ll see you again soon.