Fleets Deploy AI to Enable In-Cab Driver Coaching

A growing number of industry technology vendors have introduced forms of AI coaching directly in the cab.

A truck driver glances down at a phone. A moment later, a voice from inside the cab alerts him to put it down. However, that sound isn’t coming from a dispatcher or a safety manager, but a device mounted inside the truck, using artificial intelligence to analyze behavior in real time and coaching the driver before an unsafe behavior leads to a crash.

That kind of instant intervention is becoming increasingly common as fleets implement AI-powered, in-cab coaching technology and, in some cases, begin to see measurable safety gains.

Dohrn Transfer Co. implemented driver-facing event recorders with AI from Samsara more than a year ago. Comparing the first quarters of 2025 and 2026, the Rock Island, Ill.-based less-than-truckload carrier found that accidents in the most recent quarter dropped 15%, said Robert Howard, president and chief operating officer.

What distinguishes the current generation of in-cab systems, Howard said, is how quickly they intervene and how much feedback they give drivers without management involvement.

“They get so many nudges before it lets the company know,” he said.

The Samsara system issues real-time prompts when it detects behaviors such as phone use, speeding, harsh braking or sharp turns. Data on those behaviors is organized and scored, allowing fleets to identify patterns, reinforce improvement and address recurring risk.

That experience reflects a broader shift underway across the trucking industry. Rather than relying primarily on after-the-fact video review and disciplinary action, fleets are increasingly using AI to process video and telematics inside the truck itself. Those systems deliver immediate feedback to drivers and escalate only persistent or high-risk events to managers.

Vendors, fleets and insurers say the approach can reduce data overload, support individualized coaching and potentially lower accident-related costs and insurance premiums, all while changing how drivers experience safety technology in the cab.

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Howard

Howard pointed to Samsara’s game-like design as part of that cultural shift.

“That the system has gamification built in can be rewarding for drivers who appreciate the autonomy of self-coaching, and competing to achieve a higher score,” he said.

Dohrn Transfer is part of Pitt Ohio Transportation Group, which ranks No. 45 on the Transport Topics Top 100 list of the largest for-hire carriers in North America.

Automated Coaching

A growing number of industry technology vendors have introduced forms of AI coaching directly in the cab.

Samsara Coach, for instance, can initiate a phone call if the system detects a drowsy driver. An AI voice agent makes the call and interacts with the driver in real time, said Margaret Finch, principal product manager at the company.

“It has a two-way conversation with that driver and asks them to pull over to the side of the road, take a break,” she said.

Another element of the Samsara product is an “avatar,” which uses a customizable voice and likeness to provide a weekly recap video summarizing a driver’s performance, reviewing any safety events and offering improvement recommendations.

Last year, Motive introduced Motive AI Coach, an AI video avatar designed to deliver personalized feedback to drivers at scale. The videos feature human-like avatars intended to increase driver engagement and retention, the company said.

Gary Johnson, Motive’s head of safety and compliance strategy, said the technology moves fleets away from reactive, discipline-focused safety programs toward individualized, data-driven coaching that delivers immediate feedback and encourages driver self-correction.

He described AI as a game changer that enables a layered approach to fleet safety. That includes real-time, in-cab coaching, aggregated data for targeted training and escalation to one-on-one mentoring when necessary. The approach reduces time spent on individual coaching while extending oversight into areas such as fuel usage, compliance and workforce management, Johnson said.

In April, Motive introduced what it calls an event validation engine, which uses AI to analyze video, audio and telematics and assigns a confidence score to each event. The goal, the company said, is to minimize false positives. High-confidence events are automatically sent to a manager dashboard, while lower-confidence events are reviewed by Motive personnel before being dismissed or forwarded.

Geotab’s line of AI dashcam products is designed to balance driver privacy preferences, in-cab assistance and fleet manager oversight, said Charlie Elliott, senior vice president of marketing and marketplace.

The lineup includes its GoFocus road-facing camera, GoFocus Plus road- and driver-facing cameras, and GoFocus Pro with auxiliary cameras, all sharing a single platform with customizable settings.

Real-time in-cab alerts are generated through edge processing, meaning the system in the truck registers behaviors such as phone use and communicates directly with the driver. The immediate alerts are intended to build driver trust, Elliott said. Geotab describes the system as a private, onboard co-pilot.

The AI also flags high-magnitude events for managers, supporting closed-loop coaching in which managers review aggregated behaviors and push feedback to drivers via mobile devices.

Context Matters

During the past year, Lytx has rolled out AI-supported capabilities including fatigue detection, pedestrian detection and red-light detection, said Brendon Hill, senior vice president of products.

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(Lytx)

The company plans to enrich certain real-time coaching alerts with textual explanations of what a driver is doing and why it matters, Hill said, citing dynamic risk. One example is speeding on a dry, sunny day versus speeding in snow at night.

Another behavior closely correlated to collisions is following distance, Hill noted, and Lytx is preparing a feature designed to address speed relative to conditions.

“We’re able to do more AI now at the edge, so our devices understand not only that you’re exhibiting risky behaviors, but the context,” Hill said.

Because the AI runs on the device itself, real-time coaching does not require data to be sent to the cloud and returned, enabling immediate intervention, he said.

Isaac Instruments recently integrated its technology with software provider BeyondTrucks, a move the companies said will enhance fleet operations for mutual customers. Isaac Instruments provides driver-, road- and side-facing cameras, with AI processing split between edge devices in trucks and cloud-based systems.

The company’s real-time, in-cab coaching is also designed to encourage “eco-driving” for fuel savings while improving safety, Isaac Instruments said.

As vehicle-mounted vision systems become more capable, they generate growing volumes of detections, video and alerts, creating a new challenge for fleets, said Jean-Sebastien Bouchard, Isaac Instruments’ chief product officer and co-founder.

We’re able to do more AI now at the edge, so our devices understand not only that you’re exhibiting risky behaviors, but the context.

Brendon Hill, Lytx

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In-cab coaching can reduce that burden by warning drivers on the device and escalating only uncorrected or repeated events to servers and human reviewers, Bouchard said.

Unmanaged evidence of repeated risky behavior, he added, also can pose a significant liability risk for fleets.

Looking ahead, augmented reality and virtual reality headsets and real-time video have the potential to become more significant training tools in the transportation industry, said Syed Zaeem Hosain, founder of Aeris Communications.

Trainers could observe driver experience remotely and support AI training, he said, noting that connectivity costs could be a limiting factor for the use of continuous video or AR/VR in longhaul operations. Aeris specializes in secure cellular connectivity to support fleet telematics providers and connected vehicles and devices.

Better AI, Lower Premiums

Howard said Dohrn Transfer expects its in-cab coaching investments to eventually translate into insurance savings.

“We’re starting to see results,” he said. “We expect fully for that to turn into better experience and into better premiums.”

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Rick Reinoehl, U.S. transportation industry practice leader for Marsh Risk, agreed that systems such as telematics, advanced driver assistance systems and AI-supported in-cab coaching could ultimately help lower premium costs for carriers.

Last year, Marsh Risk introduced Marsh Road Transportation, an offering developed with Inigo and Samsara that combines insurance with telematics technology. Data from those systems can be used to inform underwriting and pricing.

AI paired with event detection, driver history and telematics can enable timely, targeted coaching and improve identification of fatigue and distraction, Reinoehl said. While there is clearer evidence linking driver alerts and advanced driver assistance systems to collision reduction, the effect of coaching on rare catastrophic events is still less documented.

“What the cameras and people have always struggled with is distracted driving and fatigue detection,” Reinoehl said. Interior cameras, he added, are playing a growing role.

The most severe incidents he has seen often involve acute fatigue, including situations in which a driver did not sleep because of illness, stress at home or a new co-driver.

Advances in AI, Reinoehl said, are now getting fleets closer to meaningful fatigue detection and closer to intervening before those risks turn into crashes.