SAN PEDRO GARZA GARCÍA, NL – Reducing road accidents and highway robberies to zero may seem like a utopia, but for Motive México it is an achievable goal if the transportation industry fully embraces artificial intelligence.

This was the point made by Omar Camacho, CEO of Motive Mexico , during the workshop on AI and Technology for a Safe, Smart, and Profitable Fleet, as part of ETYL 2025, where he shared worrying data and concrete solutions to address the sector’s main challenges.

“Freight transport represents nearly 5% of the national GDP, but theft alone generates losses equivalent to 0.5% of the total, in addition to the human and operational costs involved,” Camacho said.

He explained that a robbery occurs on the country’s highways every 24 minutes , and 40% of them originate from within organizations , reflecting the urgency of integrating more predictive and less reactive technologies.

At the same time, road safety is experiencing alarming deterioration. Mexico is now the country with the second-highest growth in road accidents worldwide.

“These are tragedies we can prevent. AI can reduce accidents by up to 80% in less than a year,” the executive emphasized.

Camacho explained that Motive develops its technology based on Computer Vision , a branch of AI that “allows systems to see, understand, and react to their environment accurately and in real time.”

In practice, this translates into a “ digital copilot ” capable of detecting distractions, drowsiness, or risky behavior, alerting the driver in seconds, and generating information for personalized training.

“Cell phones have become an epidemic of distractions. A digital copilot doesn’t tire, isn’t distracted, and can save lives,” Camacho said.

He also shared examples of how Motive’s systems learn from thousands of hours of video to identify complex human signals such as fatigue and microsleeping.

During the session, attendees—representatives of transportation and freight companies—shared experiences that reflect current gaps in visibility, monitoring, and emergency response .

They agreed that, despite the use of cameras and GPS, the processes remain manual and reactive.

“We face thefts even with cameras installed, but if the video isn’t uploaded to the cloud, we have no evidence or defense,” commented one participant.

Camacho emphasized that Motive’s vision goes beyond traditional tracking or telemetry .

“The fleet must be understood as an interconnected ecosystem. It’s not enough to know where the truck is, but why it’s there, what conditions it faces, and how to make the operation more productive in real time,” he said.

The Motive Analytics platform integrates data on fuel consumption, operator behavior, maintenance, and safety, with the ability to answer natural questions like, “How many kilometers did we drive this month?” or “Where is the diesel consumption abnormal?” , providing immediate insights for decision-making.

In addition, the company is promoting modules for digital document management and regulatory compliance , such as the monitoring of pipelines and hydrocarbon transport required by the Energy Regulatory Commission, in order to prevent fuel theft and ensure full traceability.

“Technology alone doesn’t change reality; it does when it connects with people. Every driver, every unit, and every piece of data is part of an ecosystem where artificial intelligence can save lives, protect assets, and build more humane transportation,” he asserted.

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Incorporating Artificial Intelligence (AI) into trucking is an alternative for making better decisions , focusing on productivity, and addressing the challenges of property and road safety allows for more assertive action.

Tecnomotum convened clients from the northeast region to present the topic: “From Data to Decision: Artificial Intelligence that transforms freight transportation” , and where various key messages were raised, one of them, from Pedro Rivera , CEO of Tecnomotum , who described that AI is required to take advantage of the sea of ​​alerts that are generated today through the systems that the units have, and where this type of solutions based on AI allows to identify risks in operation and not only address asset security .

“There’s more and more data out there. At Tecnomot}um , we aim to unite various systems and leverage all available information, such as ADAS systems in trucks,” Rivera said.

Pedro Rivera was emphatic that AI must be incorporated into business operations to be more efficient, make more accurate decisions, and achieve better use of resources.

Carlos Cota, Vice President of Revenue at Tecnomotum , recalled that in 2015 they began the Enlace Freightliner integration to develop a platform that would allow the use of technology for logistics purposes, but now through the incorporation of AI the goal is to make their operation simpler , with Enlace Freightliner 3.0 (EFL 3.0) .

“Intelligence now allows us to identify all alerts and which ones need to be addressed in order to avoid a potential accident, making us more assertive in our decision-making,” Cota noted.

The executive emphasized to the transporters that one advantage Tecnomotum has is the development of products tailored to the Mexican market and the real-life working conditions they face.

Carlos Cota recommended that carriers evolve by converting monitoring centers into intelligence centers, which will have the following advantages:

• Intelligent alert assignment.
• Alert segmentation by risk.
• Automation of actions.
• Neurovision and automated reports.
• Discover how to turn your monitoring center into an operational intelligence center .

While this solution is integrated into EFL 3.0, it can be implemented on any truck or tractor-trailer model to achieve the benefits mentioned.

A practical example of how Artificial Intelligence supports decision-making is the following: “It takes AI less than two minutes to analyze 60,000 alerts generated by the units; in a highly efficient action, it would take a monitor 480 hours,” described Javier Altamirano, Director of Product Marketing at EFL 3.0.

Altamirano explained that the advantages of EFL 3.0 can be described in three areas: first, the ability to group alerts into three lanes: possible vehicle theft, fatigued driving, and possible accidents, “allowing us to find the needle in a sea of ​​alerts . “

In the case of road safety, the Dangerous Driving Meta-Alert module  allows the monitoring center to reduce risk through preventive alerts. Calls are made by a robot through the Neuropanel, and actions can be automated according to the defined processes.

The previous one is the second lane, automation.

While the third lane is determined by creating alerts on cameras with AI, “this function allows us to identify the correct operator, recognize objects that should not be in the cabin, all of this is done by Motum on our supplier’s original camera, which is the added value we give to our market offering ,” Javier Altamirano asserted.

The approach presented by Tecnomotum executives generated a shift in perspective for some of the transporters present, motivating them to be more receptive in order to obtain greater benefits from Artificial Intelligence.

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