Fleets Get a Data-Driven Maintenance Upgrade

Geotab rolls out AI-driven maintenance tools to help fleets predict failures, reduce downtime, and act on vehicle data before problems escalate

10 Mar 2026

Geotab has introduced two artificial intelligence-driven maintenance tools aimed at reducing unplanned vehicle failures in US commercial fleets, as operators face rising costs and persistent downtime.

The company unveiled the tools, Work Order Management and Fault Code Enrichment, at its Connect 2025 conference in Orlando in February. Both are integrated into its MyGeotab platform and target a shift from reactive repairs to predictive maintenance.

The move comes as an estimated 55,000 vehicles are towed daily on US roads due to mechanical failures. Fleet maintenance costs also rose by 7 per cent in the first half of 2024, according to industry data.

Work Order Management consolidates scheduling, repair tracking and cost reporting into a single system, replacing manual processes and fragmented software. It uses predictive analytics to identify vehicles at higher risk of failure, allowing operators to intervene before breakdowns occur.

The second tool, developed with diagnostics group Noregon, addresses the volume and complexity of vehicle fault codes. Heavy-duty trucks can generate hundreds of such codes each month, many of which require manual interpretation.

Geotab’s Fault Code Enrichment uses AI to classify these signals, assigning severity ratings and recommending corrective actions. It also estimates potential downstream effects on components, allowing fleet managers to decide whether a vehicle should stop immediately or continue operating until scheduled maintenance.

Sandeep Kar, chief strategy officer at Noregon, said the ability to prioritise faults was central to the system’s value. “The ability to distinguish minor issues from those threatening breakdowns or compliance violations is central to the tool's value,” he said.

For US carriers operating under Federal Motor Carrier Safety Administration rules, vehicle condition has direct implications for safety scores and regulatory audits.

The launch reflects a broader shift in telematics from data collection towards decision support. While fleet systems have long generated large volumes of data, operators have often struggled to translate it into actionable insights.

By embedding AI into maintenance workflows, Geotab is seeking to improve vehicle uptime and reduce costs, as fleet operators face increasing pressure to manage efficiency and compliance.