AI in fleet management is no buzzword—it’s already powering many of the most advanced digital solutions in the marketplace.
For example, AI-enabled dashcams alert drivers when they identify risky driving behaviour like smoking, fatigue or phone usage. With predictive maintenance tools, fleets analyse their vehicle data to proactively address potential issues, minimising downtime and unplanned costs. And advanced algorithms optimise route planning for faster delivery times and reduced fuel consumption.
But this is just the beginning. It’s certain that AI will only become a greater enabler of more powerful fleet solutions in the future.
Survey: The outlook on AI in fleet management
We recently surveyed 1,800 fleet decision makers across the world to understand the technological trends shaping the future of mobility. Our findings show that fleet managers expect AI and machine learning to have the biggest impact on their business in the coming five years.
You can see a sample of the survey results below. Prefer to see the whole report instead? Download our Fleet Digitisation Report now.
Do you have any plans to use AI in any part of your fleet management operation?
| We currently use AI in our fleet management | 23% |
| We don’t currently use AI in our fleet management but plan to in the next five years | 35% |
| We don’t currently use AI in our fleet management but may at some point in the future | 34% |
| We have no plans to use AI in our fleet management | 9% |
Country-to-country there were some interesting variations. The most enthusiastic countries about AI are Belgium, Australia, Colombia, Italy, Mexico, South Africa and the US. In every one of these regions, over 60% of fleet managers either use it or plan to use it soon.
On the flipside, the UK, the Netherlands and the UAE are the only countries where the majority of fleet managers do not plan to use AI in the next five years at all.
How do you expect AI to impact/continue impacting your fleet management in the coming five years?
| Optimise route planning and logistics | 62% |
| Improve driver safety and behaviour analysis | 56% |
| Enhance predictive maintenance and asset management | 55% |
| Reduce my operating costs | 54% |
| Automate administrative and compliance tasks | 51% |
| Increase fuel efficiency and reduce emissions | 50% |
Fleet managers see many potential benefits in AI, from better logistics to higher levels of safety, simplified maintenance and lower costs. What do they say about the potential negative consequences?
On a scale of 1 to 5, how concerned are you about the impact AI might have on your role as a fleet manager?
| 5 (Extremely concerned) | 9% |
| 4 | 14% |
| 3 | 35% |
| 2 | 25% |
| 1 (Not at all concerned) | 16% |
As we see, only 21% of fleet managers say they are particularly concerned about AI and its influence on their role. Equally interesting is how fleet managers who expressed concern answered the next question.
Which concerns do you have regarding the impact of AI on your role as fleet manager?
| It will require complex integration to implement | 53% |
| It will increase the risk of data security breaches | 49% |
| I think it might threaten my drivers’ jobs | 36% |
| I think it might threaten my job | 31% |
| I don’t trust AI to always make the best decision | 29% |
So, the worries fleet managers have about AI have more to do with potential operational complexity or security issues than with threats to people’s livelihood or trust in the ability of the solutions themselves. This suggests that as new AI-enabled solutions evolve—and support is available to ensure it is utilised safely and seamlessly—even these fleet managers will come around to its transformative power.
Where AI and fleet optimisation meet
Soon, AI-enabled assistants will enable telematics users to get the precise insight they need in any situation—and quickly. Rather than dig through a series of reports or play with a set of filters, for example, a fleet manager could simply type “Give me the statistics for all driving times and total mileage for my drivers, aggregated for the last five months” and receive this overview in seconds.
AI will also make comparing and interpreting data and trends across different parts of a fleet or different time periods easier and more valuable, complete with industry benchmarking, gap analysis and suggested plans of action to improve performance.
But AI-enabled fleet management goes beyond merely analysing the past to optimising fleet performance in the present. When planning the job schedule for the day, the platform could quickly determine the right driver, the right vehicle, the right route, the best way to utilise cargo space and all other relevant details to create a fully optimised journey for each specific job. It could similarly be applied to optimising a host of other essential fleet tasks, from vehicle maintenance to compliance management.
Introducing: AI Assistant by Webfleet
We’ve introduced a beta version of Webfleet AI Assistant to a select group of customers in OptiDrive 360, our driving performance analysis tool. The Webfleet AI Assistant leverages generative AI to deliver quick, data-driven insights to fleet managers.
In testing the beta version of Webfleet AI Assistant, our customers are discovering how the tool can help them make smarter, faster decisions around cutting costs, improving safety, reducing fuel consumption and boosting productivity.
With data analysis as simple as typing a sentence, more and more people across a fleet’s business can generate tailored, actionable insights. Since the Webfleet platform is protected with the highest standard for data security in Europe (ISO/IEC 27001:2017), this added convenience and speed does not come with any extra risk of compromising sensitive fleet data.
Speaking of fleet data: To get the maximum benefit from AI, your fleet needs access to the right data sets. The more data you can feed the solution on things like your logistics operations, vehicle information and maintenance history, the more value you can unlock with AI. That’s why our beta version runs on lots of historical data.
Eventually, as more and more tasks become automated and the solution becomes intelligent enough to solve more sophisticated problems faster, fleet managers may have very little need for interaction with the fleet management platform at all, freeing them to focus on other tasks in their business.
Want to know more about the beta version of Webfleet AI Assistant? Watch our 1-minute intro video:
