The good news is that AI and digital twin technology have moved beyond mere hype. Real fleets are using these tools right now to attack the problems that actually matter: empty miles, failed deliveries, and insurance claims that shouldn’t exist.
Here’s what that looks like in practice.
1. Simulate before you spend
If you’re planning an EV transition based on spreadsheets and manufacturer estimates, you’re gambling with multi-million-dollar investments. Real-world conditions like winter range loss, unexpected charging delays, or actual route variability destroy even the best projections.
And with new emissions disclosure rules like California’s SB 253 raising the bar for transparency, the margin for error is shrinking fast.
Digital twins solve this by creating a virtual replica of your entire operation using your actual TMS and telematics data. Before you buy a single EV, you can:
- Test different vehicle models on your actual routes
- Calculate true TCO including maintenance, downtime, and charging costs
- Simulate peak demand scenarios and grid capacity constraints
“You pilot in software before you commit in the real world,” says Dean Marris, EROAD’s Chief Data Science Officer. “That means fewer surprises, faster decarbonization, and better service.”
Eventually, these digital twins are able to run continuously in the background as your AI co-pilot detecting problems before they happen. Picture this: an EV is burning battery faster than expected, so the system runs multiple simulations in seconds and automatically reserves a fast charger or reroutes to a closer depot.
2. Stop losing money to empty miles, cargo spoilage, and excessive dwell time
You already know the big three profit killers:
- Empty miles (deadhead mileage rose to 16.7% in 2024)
- Cargo spoilage (food losses during transport and storage reached $210 billion in 2022)
- Dwell time (In 2023, fuel burn from idling cost the industry over $286.1 million)
Traditional dispatch can’t prevent these losses because humans are not able to process the variables fast enough. But AI can. Here’s how it works:
- Load matching: Advanced algorithms pair available capacity with loads in real-time, considering driver hours, equipment type, and return routes. The system finds backhauls your team didn’t have time to search for.
- Cold chain protection: Unlike traditional temperature monitors, AI technology like CoreTemp learns the normal performance patterns of each reefer unit. It identifies early warning signs of failure to give you time to act before costly spoilage occurs.
- Idle reduction: Machine learning identifies patterns like which routes, drivers, or conditions create excess idle time, and provides specific optimizations, rather than general fixes.
“Instead of just providing reefer out of range or shut down alerts, the system’s using actual machine learning based on, say, the previous two weeks’ history, and it provides that blacklist of reefer trailers to focus on, then it takes action,” Dean explains. “You fix problems before customers ever know there was one.”
3. Reduce insurance costs and protect your drivers
Rising insurance costs and lengthy claims eat into profits and affect driver morale. AI visibility changes that, giving fleets the accurate incident data they need to protect margins, settle claims quickly, and keep good drivers on the road.
AI-powered video systems like EROAD’s Clarity Edge AI are changing that. By combining smart risk detection with multi-view visibility, fleets get a complete picture of every incident — and most importantly, prevent many from happening at all.
- Incident exoneration: Fleets using multi-camera systems report exonerating drivers in up to 80% of claims. That means faster claim resolution and lower premiums.
- Driver confidence: When drivers know they’re supported — not just surveilled — they stay longer. Investing in their safety pays off in lower turnover and higher uptime.
- Smarter insights: AI automatically classifies risky behaviors and events, helping safety teams focus coaching on where it matters most.
Every safer mile adds up to lower premiums and a culture that drivers actually want to be part of.
Building the future together
The impact of AI goes beyond individual fleets. What’s becoming popular now is a more connected, data-driven ecosystem where collaboration between all industry players benefit everyone.
Shared operational data helps fleets cut empty miles, boost utilization, and accelerate learning across the industry. Partnerships with OEMs, shippers, and technology providers make it possible to build future-ready infrastructure faster than any single fleet could on their own — like expanding EV charging capacity, optimizing energy use, and modernizing logistics hubs.
As Volvo Group’s CTO Lars Stenqvist says, “If you’re viewed as the company with whom others want to join, with whom others want to partner, then that will be a true competitive edge to your company.”
Those who have embraced open collaboration are already seeing the payoff: reduced operational costs, a more reliable supply chain, and happier customers.
Start now or play catch-up later
Every fleet says they want to run smarter. The difference is who’s taking action now. The fleets who thrive will be the ones who started building these capabilities today. As Craig Marris, EROAD’s Chief Sustainability Officer, puts it, “The winners in 2030 will be the fleets that prove profitability, safety, and sustainability can reinforce one another.”
Want to know more about how fleets are using AI and digital twins to drive real results? Hear from Dean Marris and Craig Marris on the Loaded and Rolling podcast as they explore how technology is reshaping fleet safety, sustainability, and profitability
