Rising prices, environmental awareness, and the rapid evolution of artificial intelligence (AI) have all led to the increased adoption of fleet management technology. Verizon Connect’s 2025 Fleet Technology Trends report found that over the last five years, at least 4 out of 5 respondents said they use at least one form of fleet technology.
Big data and AI have dozens of applications in fleet management. Integrating these tools into your business practice can reduce maintenance costs, improve routing, and create safer working conditions for drivers. And many of these advanced tools are already accessible to smaller merchants. Here’s how AI and big data can help improve your operations.
How AI and big data are transforming fleet operations
AI and big data are helping fleet operators meet a number of persistent challenges. Verizon’s report identified increasing costs as the No.1 issue — 77% of respondents said costs were their primary concern. Other obstacles include driver shortages, inefficiencies in scheduling, and difficulty meeting customer demand.
AI and big data are already making big progress in resolving these issues. For instance, GPS tracking and other telematics tools have a positive return on investment (ROI) of 47%.
“For fleets of all types, GPS fleet tracking can have a wide-reaching impact on reducing overhead costs, including fuel, labor, accidents, maintenance and insurance,” wrote Verizon.
Let’s dive deeper into how predictive analytics and AI can help fleet operations work more efficiently and sustainably.
[Read more: How to Keep Track of Company Vehicle Use]
Businesses have started leveraging AI to improve route planning and optimize fuel use. AI can process live traffic, weather, and road condition data to suggest the most efficient routes.
Predictive analytics: Reducing maintenance costs and improving uptime
Predictive analytics help fleet managers identify when vehicles need to be taken off the road for service, preventing unanticipated breakdowns and delays.
“Predictive maintenance [leverages] real-time data from vehicles to forecast when components will fail or when service is genuinely required,” wrote Fleetpoint. “According to a report from Automotive Fleet, predictive maintenance has been shown to reduce overall maintenance costs by up to 20%, while simultaneously reducing unplanned downtime by up to 50%.”
Predictive analytics also help fleets avoid emergency repairs, which can cost between $350 and $700 per call. On average, this unplanned downtime can result in lost revenue of $448 per hour.
By analyzing data from vehicle sensors, telematics, and fault codes, predictive analytics identifies potential problems before they escalate. Not only can this improve uptime, but it also contributes to a safer working environment for drivers.
[Read more: Fleet Management Tools for Small Businesses]
AI-powered routing and fuel optimization
Meanwhile, businesses have started leveraging AI to improve route planning and optimize fuel use. AI can process live traffic, weather, and road condition data to suggest the most efficient routes. For instance, when an AI tool detects building traffic, it can reroute a vehicle to save time and reduce the additional fuel consumption that happens during long detours and idle times.
“With this kind of route optimization, you can ensure timely deliveries, reduce the need for extra trips and lower fuel costs,” wrote Geotab. “Plus, your vehicles will experience less wear and tear.”
Some vendors estimate that AI-powered route optimization can reduce fuel and related expenses by up to 20%. And more on-time deliveries lead to more satisfied customers and a greater opportunity to increase customer retention.
Using data to monitor driver safety and performance
Telematics systems, dashcams, and driver monitoring systems can all be utilized to improve driver safety. These tools can capture key metrics such as:
- Speeding events.
- Harsh braking or rapid acceleration.
- Unsafe maneuvers or aggressive driving.
- Seat belt usage.
- Fuel efficiency.
Fleet managers can also monitor how long drivers have been on the road to ensure no one is at risk of falling asleep at the wheel. Some of these tools are accepted by insurance companies to lower your premium costs.
Challenges and considerations when adopting AI in fleet management
Today’s technology for smarter fleet management has proven its value. Verizon’s research found that fleets see an ROI often within six months after implementation. However, it’s worth noting that telematics and other tools can be a substantial investment. Initial costs range from $2,000 to $10,000 per vehicle, depending on the level of automation and hardware included.
As you explore your options, consider the size of your fleet, the pricing options for hardware and software, how these tools integrate with your existing systems, and the scalability of your solution.
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