How AI is reshaping the role of video telematics in fleet management

Gurtam is embracing modern technology, and AI is definitely part of the journey. We’re publishing this article on World AI Appreciation Day, July 16, to highlight how artificial intelligence is changing real businesses globally.

We’ve come a long way since the early days of GPS tracking. What began as simple location-based monitoring has evolved into complex, integrated systems that combine video, analytics, connectivity, and real-time decision-making. At the center of this transformation lies artificial intelligence.

For years, fleets have used cameras to capture footage useful for training, insurance claims, and incident investigations. However, these systems relied heavily on human eyes. Someone had to sit with hours of footage to identify what happened.

Today, that approach is no longer scalable. Commercial fleets generate vast amounts of video data every day. How can one make sense of it all? That’s where AI comes in. 

In this article, we will explore the tandem of AI and video telematics and see how they bring real-life business results to commercial fleets.

What AI-powered video telematics looks like

In fact, the industry began integrating AI into video solutions well before the recent rise of generative AI. At Gurtam’s TelematiX conference back in 2019, discussions around object recognition, in-cabin monitoring, and behavior analytics were already front and center.

Today’s AI-driven systems are more than just cameras. Equipped with object recognition, facial analysis, and real-time behavior interpretation, these devices capture, analyze, and act.

AI identifies if a driver is fatigued, distracted, using a phone, or exhibiting signs of aggressive driving. It distinguishes between a sudden stop caused by traffic and hard braking due to a near-collision. It can tag clips, generate smart alerts, and push relevant insights to fleet operators in seconds.

Modern hardware supports this intelligence. The assortment of video telematics equipment is very rich as of 2025: dual-facing dashcams for in-cabin and road views, 360° multi-camera setups, ruggedized builds for harsh environments, and more. Most importantly, edge AI, which processes data directly on the device, is making real-time response possible without overloading cloud systems.

Turning video into action: key applications for fleets

Let’s look at how AI video telematics is actively reshaping day-to-day fleet operations.

That’s only a general overview: in reality, even more features provided by video telematics platforms are becoming available to businesses. For example, through solutions like AI-powered risk segmentation, fleets can automatically group drivers by behavior profiles and intervene early, before incidents happen.

👉 Read the case study on how a tanker transport company from Honduras eliminated accidents thanks to AI-powered cameras integrated in their fleets. 

The measurable results of AI-powered video for fleets

"That all sounds great," any business owner might say. "But what about the cost? These advanced MDVRs, servers, and software — how are they going to affect our bottom line this year? Will we actually see a return, directly or indirectly?"

With AI-backed video telematics, those outcomes are tangible. Let’s look at some of them:

• • • Fewer accidents. AI-powered interventions lead to safer driving. Not only can drivers get immediate feedback on their actions, but their overall performance can also be analyzed and assessed, providing them with ideas on how to improve their work. Better driving habits lead to fewer accidents.
      
      

    • Lower insurance premiums. When video footage clearly shows what happened in an incident and proves your drivers weren’t at fault, it helps reduce false claims. Fewer accidents and payouts mean insurance companies see your fleet as lower risk, which often leads to better rates. Some insurers even partner directly with telematics providers for proactive safety programs.
      
      

    • Better coaching and retention. Real-time feedback improves driver behavior, while AI-generated summaries make post-trip coaching more efficient and fair. Drivers are more likely to engage when they know they’re being evaluated objectively.
      
      

    • Time saved. Reviewing video manually is time-consuming. AI reduces this by showing only the clips that contain crucial information, allowing fleet managers to focus on more important things that can’t be solved by software yet.

👉 Read the case study on how AI cameras helped a Mexican transportation company better resolve claims with customers and insurance companies.

But it’s not all smooth roads. Challenges to consider

Despite the benefits, AI video telematics isn’t a plug-and-play solution. It requires a clear understanding of your fleet’s needs and the resources to implement it effectively.

Cost and value

Advanced AI cameras aren’t cheap. However, for most medium-to-large fleets, the ROI typically justifies the investment within 6 to 12 months due to savings in insurance, reduced accidents, and improved operational efficiency. For smaller fleets, more affordable options exist, especially when working with providers who understand scaling needs.

Data privacy and legal concerns

Different countries, as well as states or regions, have varying laws regarding video monitoring. Face recognition, in particular, can be sensitive. AI systems must be configurable to comply with these rules, and fleet owners should be aware of their local obligations. And sometimes, drivers can simply refuse to be recorded with their faces visible.

Integration and complexity

Even the smartest AI camera won’t deliver results on its own. You still need to select the right hardware, connect it properly, ensure reliable connectivity and storage, and integrate everything with your existing fleet management system. That’s where a skilled telematics service provider comes in; they make sure all these moving parts work together seamlessly, from installation to data flow and real-world performance.

Training and onboarding

Technology is only valid if people know how to use it. That includes both fleet operators and drivers. A successful rollout involves clear training, defined policies, and ongoing support.

What’s next: the frontier of AI and video telematics

We’re just at the beginning of what AI and video can do together. From our 20+ years of experience in the industry, we would like to highlight a few key trends that point to where things are headed:

• • • Integration with ADAS. AI video is starting to blend with advanced driver assistance systems, combining visual inputs with radar, lidar, and proximity sensors for enhanced collision avoidance.
      
      

    • IoT and predictive maintenance. Imagine combining video analysis with sensor data from the engine, tires, and brakes. That’s where we’re headed, spotting not just risky driving but early signs of mechanical failure. Together, video and sensor data help fleets not only detect issues but also understand their causes and act more quickly.
      
      

    • Edge (on-device) vs. cloud processing. More intelligence is shifting to the edge. Cameras themselves are doing the heavy lifting, making split-second decisions and sending only relevant data to the cloud, saving bandwidth and ensuring faster responses.
      
      

    • Smarter context awareness. AI is evolving not only to detect events but also to better and more accurately understand the context surrounding them. It will soon be able to perfectly distinguish between a planned delivery stop and a roadside emergency or differentiate erratic driving caused by reckless behavior from that triggered by poor weather conditions. This means fewer false positives and far more accurate, relevant alerts, all of which lead to smarter decisions and quicker interventions.