The various potential benefits of using artificial intelligence (AI) to aid fleet management have been widely discussed, but the industry has in large part been waiting for the technology available to catch up with the claims of what it will be able to achieve.

Indeed, while there are an increasing number of use cases for AI, the same can be said across most sectors. Nonetheless, in a poll of 386 people as part of GlobalData’s Tech Sentiment Polls Q4 2023 across its network of B2B websites, 92% responded that AI would either live up to all of its promise or that it was hyped but that they could still see a use for it.

Notably too, Jensen Huang, founder and CEO of US tech firm NVIDIA, said with the release of the company’s fourth-quarter financial results on Wednesday (21 February): “Accelerated computing and generative AI have hit the tipping point. Demand is surging worldwide across companies, industries and nations.”

For fleet management, the potential benefits of AI variously include optimised route planning and hub locations, driving and fuel efficiency refinements, predictive maintenance, improved inventory management, real-time tracking and compliance management, among other things. As such, there is the promise of a significant impact within the industry, and Huang’s comment suggests it – and others – are on the cusp of that.

Wialon, which provides a fleet management platform based on telematics and internet of things technologies, is well placed to understand and quantify what the development of AI within the industry will look like.

Aliaksandr Kuushynau, head of the company, which itself is part of the Lithuania-based Gurtam GPS software tracking group, spoke to Leasing Life about the current state of AI in the industry, what the future holds and what benefits and challenges can be expected.

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Do you think AI has hit a tipping point?

Kuushynau: The integration of AI into fleet management software represents a crucial technological shift, poised to make fleet operations more efficient and effective. We haven’t yet reached a tipping point, but I can see that happening in the next one to two years.

Overall, the incorporation of AI-based technologies and tools in fleet management software marks a significant advancement in the industry. It not only simplifies the work of fleet managers but also enhances the overall efficiency, safety, and cost-effectiveness of fleet operations. As AI continues to evolve, its role in reshaping fleet management will likely become even more pronounced, driving innovation and operational excellence in the sector.

What do you think we can expect in the short- to mid-term?

AI-driven tools in fleet management software can automate and optimise numerous aspects of fleet operations. For instance, AI can enhance route planning by analysing traffic patterns, weather conditions, and vehicle performance data, to suggest the most efficient routes, saving time and reducing fuel costs. Predictive maintenance is another area where AI plays a crucial role. By analysing data from vehicle sensors, AI can predict when a vehicle might need maintenance before a breakdown occurs, reducing downtime and maintenance costs.

Crucially, AI also significantly improves safety management in fleets. By analysing driving patterns and behaviour, AI can identify risky behaviours and provide insights for driver training and safety programs. This not only improves overall fleet safety but also reduces the likelihood of accidents and associated costs.

What challenges and benefits do you think we are likely to see?

We will see major benefits in the realm of decision-making, as AI can process vast amounts of data to provide fleet managers with actionable insights, helping them make informed decisions about their fleet. This includes vehicle utilization, cost analysis, and compliance with environmental and safety regulations. Furthermore, AI is instrumental in managing the complexities of modern fleets, especially as they transition to include electric and autonomous vehicles. AI can efficiently manage charging schedules for electric vehicles and integrate with advanced driver assistance systems in autonomous vehicles.