Artificial Intelligence (AI) isn’t just a buzzword anymore—it’s already at work helping fleet managers identify trends, predict failures, and make smarter decisions. The capabilities of AI are set to get even more exciting, particularly with the introduction of plain language queries and intuitive data interrogation. In a wide-ranging discussion with Fleet News Group, Chris Martin, Senior Manager of Solutions Engineering – APAC at Geotab, shared how AI is reshaping the fleet management landscape today and what the future might hold.
AI in Fleet Management: From Data to Insights
Fleet management has always been data-heavy, with information flowing in from telematics devices, sensors, and more. But the challenge has been in making sense of this data—finding patterns, understanding trends, and predicting issues before they become costly problems. AI is now stepping up to tackle these tasks, making fleet management more proactive and efficient.
According to Martin, “We consider ourselves more of a data company now, with over four and a half million vehicles connected to our platform globally, reporting every day. With that comes a lot of data—more than 75 billion data points every day, in fact.” But managing this sheer volume of information isn’t easy, which is where AI comes in. Martin explains, “AI helps us process and analyse this data, finding trends that would be difficult for a human to spot.”
AI is particularly useful for predictive maintenance, where the focus is on identifying potential failures before they happen. Martin shares a success story: “We’ve implemented predictive battery failure technology, which has been a game-changer for one of our large delivery fleet customers. By analysing cranking voltages and other indicators, we were able to reduce on-call battery replacements by 20-25%. The AI models help us understand what a problematic vehicle start looks like and then alert the fleet manager to replace the battery before it fails.”
What AI Brings to the Table Today
AI isn’t just about predicting mechanical issues—it’s also about helping fleet managers understand broader trends and make informed decisions. AI can analyse driving patterns, fuel usage, and vehicle wear, helping managers see where improvements can be made.
Martin emphasises, “AI is great for identifying trends, whether it’s risky driving behaviours, fuel inefficiencies, or component wear. It helps fleet managers stay ahead of the game by highlighting potential issues before they turn into bigger problems.” The key, he adds, is making data actionable: “It’s not enough to have the data—you need to know what to do with it. AI helps by turning raw data into actionable insights, making it easier for fleet managers to make informed decisions.”
By integrating AI into telematics, fleet managers can get insights on everything from safety risks to maintenance needs. Martin describes it as “moving from dots on a map to sophisticated decision-making tools.” And it’s not just for large fleets—small and mid-sized fleets can also benefit from AI-driven insights that lead to better efficiency and cost savings.
The Future: Plain Language Queries and Easier Data Interrogation
While AI is already delivering significant benefits, the next big leap will be in how fleet managers interact with data. Martin explains that Geotab is currently testing a product called “Geotab ACE,” which uses AI to allow users to make plain language queries.
“We’re used to interfacing with language models like ChatGPT in our everyday lives, and it’s exciting to bring that to fleet management,” he says. “Imagine a fleet manager asking, ‘What’s my fuel consumption over the last three months?’ and getting an immediate response without having to run complex reports.”
This kind of AI-driven data interrogation means that fleet managers won’t need to be experts in running reports or filtering spreadsheets. Martin elaborates, “You don’t need to know where to find the data or how to process it—just ask the question, and the system will deliver the answer. It’s going to save time and make fleet management more accessible, even for those who aren’t tech-savvy.”
The AI interface will be able to handle more complex questions, too. “For example,” Martin says, “fleet managers will be able to ask, ‘Which vehicles have the highest fuel consumption?’ or ‘Which group of drivers is showing the highest safety risk?’ The AI will not only pull up the data but help analyse it, giving managers a clearer picture of what’s happening in their fleet.”
AI and the Road Ahead: Smarter, More Efficient Fleets
As AI continues to develop, its applications in fleet management are set to expand even further. Martin believes that we’re moving towards a more predictive and personalised approach to fleet management: “We’re seeing AI being used not only to predict failures but to help fleets adopt condition-based maintenance. This means replacing parts or servicing vehicles only when needed, which reduces waste and has a positive environmental impact.”
AI can also help fleets manage electric vehicles more efficiently. “With AI, we can analyse EV battery performance, charging patterns, and energy consumption, making the transition to electric fleets much more manageable,” Martin notes.
But the most exciting development, according to Martin, is AI’s potential to simplify fleet management. “The ultimate goal is to make it easy for fleet managers to get the insights they need without getting bogged down in data. AI is here to help with that—whether it’s identifying trends, predicting failures, or making data easier to access.”
Artificial Intelligence is already making a big impact in fleet management, from predicting battery failures to simplifying complex data analysis. But the journey is just beginning. With AI-powered tools like Geotab ACE, the future looks set to be even more intuitive, with plain language queries and smarter decision-making at the forefront. As Martin puts it, “AI isn’t here to replace fleet managers—it’s here to make their jobs easier, more efficient, and more informed.”
