By Aliaksei Shchurko, CEO at Gurtam

Electric vehicles (EVs), self-driving cars, and artificial intelligence (AI) are revolutionizing commercial fleets. Naturally, they are also transforming the work of telematics service providers and the whole fleet management market. And as with any revolution, this presents both threats and opportunities..

I’m Aliaksei Shchurko, CEO at Gurtam and creator of Wialon, one of the world’s largest telematics and IoT platform. Together with Wialon, my company develops a telematics backend flespi and a set of easy-to-use GPS tracking apps for individual users GPS-Trace. Currently, all three products connect and collect data from 4.5 million vehicles and other assets. At Gurtam, we use this vast amount of information to uncover real trends and plan platform improvements accordingly.

So let me share my vision for telematics evolution over the next 10 years.

Myth #1: OEM Telematics Challenges the Dominance of Aftermarket Telematics

The competition between Original Equipment Manufacturer (OEM) telematics and aftermarket solutions has been ongoing for years. Some argue that car manufacturers will more actively embed telematics tools in their vehicles from the factory. They say that it will gradually reduce the aftermarket telematics market share.

The reality? I doubt OEM telematics will experience significant growth from its current small fraction. It’s just too hard to compete with aftermarket telematics, which offers high quality, competitive pricing, and a wide range of functionalities.

So, I expect that both aftermarket telematics and OEM embedded solutions will coexist, but aftermarket options will continue dominating the market.

Myth #2: Electric Vehicles (EVs) Transform Telematics

Electric vehicles (EVs) are gaining popularity worldwide, and the numbers speak for themselves. This has led some experts to believe that EVs will revolutionize telematics.

But I disagree.

At the end of the day, electric vehicles are just vehicles. Although they introduce extra parameters to monitor, such as battery charge and energy consumption, the core function of telematics remains to track their location and performance. Modern platforms like Wialon seamlessly integrate these new parameters into their functionality. So, I don’t see a telematics revolution caused by EVs.

Myth 3: Autonomous Driving Sparks a Fleet Management Revolution

Semi- and fully autonomous vehicles are a hot topic. But like with EVs, I don’t expect a significant shift from autonomous vehicles anytime soon.

First of all, let’s not rush with them. Until we solve security and technology problems, most fleets won’t use self-driving cars. I think it will take at least ten years before we see big changes in this area.

In telematics, autonomous driving won’t bring significant changes either. Customers will still need to keep an eye on vehicle location, mileage, and other vehicle performance parameters. So, while telematics will require some adjustments, it will continue to fulfill the same role as before.

Now, after debunking some myths, let’s talk about something truly groundbreaking: Artificial Intelligence (AI). Yes, AI will change the world and, as a result, reshape telematics because it’ll have to adapt to this new world.

So, a real revolution and the key trends in telematics come from AI technology. Let’s take a closer look at them.

Trend #1: AI Becomes More Context-Aware

AI thrives on data. Take ChatGPT, for instance. It’s been trained on 70 billion data points to carry out its primary task – effectively predicting the next word. In a nutshell, it functions like the autocomplete feature on your phone, but on a much larger scale, drawing from billions of words.

However, ChatGPT’s responses are too generic because it lacks contextual understanding. That’s why you can’t solve specific tasks using ChatGPT solely.

To deal with this challenge, we’ll see more AI models trained on task-specific datasets. Platforms like Wialon play a key role here because Wialon provides data on every aspect of a particular area – fleet management. When AI integrates with this data, it learns patterns and generates accurate and context-aware responses for specific queries.

Trend #2: The Number of AI Personal Assistants Keeps Growing

When you have an AI model trained on a specific dataset, it’s time to integrate its functionality into a solution. This is why I anticipate a surge in innovative personal AI assistants in the near future. Industry giants such as Microsoft and Amazon have already presented such products. Soon, we’ll see other companies joining the stage with their own versions of Copilot and Amazon Q.

Imagine this scenario: a powerful AI chatbot, trained on Wialon’s documentation and vast data, comes integrated with additional tools like reporting functionality and configuration assistance. These tools enhance the chatbot’s capabilities. For example, it swiftly detects anomalies in reports or helps configure devices. This will completely transform the way users interact with the Wialon platform.

Trend #3: AI Simplifies Everything

Alright, we’ll have powerful AI assistants trained on specific and vast data sources, capable of staying context-aware. What’s the main benefit? Simplifying routine tasks. And the trend is that we’ll see this on a larger scale in 2024-2026.

As an example, let’s consider the classification ability of telematics AI-powered systems. They are great at analyzing many parameters and categorizing objects into suitable groups.

For instance, if you want to determine whether a driver is engaging in harsh driving or not, you’d typically need to assess dozens of driving characteristics. For a human, this task could take some time, but AI accomplishes it in seconds. It interprets parameters in a report, classifies driving styles, helps establish bonuses or penalties for drivers, and offers personalized recommendations.

Another example involves computer vision. AI empowers systems to identify and troubleshoot issues in an image, much like a human would. Imagine this scenario: you need to install a GPS tracker into a client’s vehicle. Instead of struggling, you can snap a photo of the car and let AI identify the correct wires and guide you on the necessary tests. It’s as simple as that.

Bottom Line

The telematics landscape is exceptionally dynamic today. OEM telematics, EVs, and autonomous driving influence fleet management. But AI changes it at its core.

With AI heavily dependent on data, our role as vehicle data suppliers becomes even more important. This shift presents new opportunities for all involved.