Logistics operations in Mexico face increasing pressures that force companies to rethink the management of their fleets, in an environment where costs, insecurity and operational efficiency have become determining factors, explained Luis Larrea, senior regional manager of Field Engineering at Samsara Mexico.
At The Logistics World Summit & Expo , Larrea explained that eight out of every ten products consumed in the country are transported through the logistics sector , while 72% of the national economy depends on foreign trade , highlighting the importance of trucking to economic activity. However, this dynamism coexists with rising costs: fuel prices have increased by 16.7% , while insurance premiums have risen between 15% and 20%.
Adding to this context is the issue of insecurity. Between January and October 2025, 5,200 robberies were recorded on Mexican highways , according to data from Samsara, with estimated losses of between 7 and 10 billion pesos annually.
Given this scenario, technological adoption is becoming increasingly important. Currently, 48% of fleets already use artificial intelligence (AI) , although its implementation requires clear objectives and a defined strategy to generate value in operations.
One of the main challenges remains fuel, which can represent between 30% and 50% of operating costs . In this respect, even marginal reductions can translate into significant impacts on profitability.
Operational visibility is positioned as a key element. Tools such as telematics, process digitization, in-cab cameras with alerts , operator training programs, and monitoring systems allow for improved operational control, optimized routes, and more efficient cost management, Larrea explained.
In particular, measuring idling speed and fuel consumption becomes critical . Identifying unnecessary expenses, analyzing driving habits, and differentiating between productive and unproductive idling allows for performance improvements, cost reductions, and real-time operational visibility.
Concrete examples reflect these benefits. Companies like Potosinos have reported a 23% increase in delivery time productivity , as well as a 20% reduction in fuel leaks and a 7% reduction in operator turnover .
In terms of fleet utilization , monitoring key performance indicators—such as productive hours, unit usage, maintenance, and route management—allows for progress toward more efficient operations. This translates into reduced operating costs, fewer units out of service, and improved asset management.
In this process, AI is positioned as a cross-cutting enabler that impacts various areas of the operation. From operators, with vehicle inspections, document interpretation, and in-cab monitoring, to maintenance and administrative teams, where this technology facilitates route management, report generation, invoicing, and order tracking.
The benefits are also reflected in financial and safety indicators. One example is PROAN , which achieved an 80% reduction in freight collection time and a 64% decrease in speeding violations , in an operation with more than 450 vehicles and over 70 years of experience .
Larrea emphasized that the combination of technology, data, and discipline in measuring indicators is emerging as the path to strengthening efficiency, reducing costs, and improving the competitiveness of the trucking industry in Mexico .
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