From Range Anxiety to Real-Time Insight

AI-driven analytics are steadily helping US electric fleets manage routing, charging, and maintenance as EV operations scale

15 Nov 2025

AI and advanced analytics are taking on a growing role in the management of US electric vehicle fleets, as operators grapple with the practical demands of running electric trucks and vans at scale.

Rather than prompting rapid change, these tools are being adopted gradually to support day-to-day decisions on routing, charging and maintenance. Fleet managers say analytics platforms are helping them deal with the operational complexity that comes with electrification, particularly as vehicle numbers rise.

Over the past year, technology providers have expanded software designed to address persistent challenges such as range planning, charging availability and energy costs. Many fleets are moving away from fixed schedules and manual monitoring towards systems that analyse vehicle and charger data in near real time. This allows operators to decide which vehicles to deploy, when to charge them and how to adjust routes to limit delays or unnecessary expense.

Several large providers have positioned analytics at the centre of their offerings. Geotab has expanded its EV-focused telematics and analytics tools to provide insights into energy use, charging behaviour and vehicle performance. Samsara has integrated EV data into its broader fleet intelligence platform, enabling operators to monitor electric and combustion vehicles together. On the infrastructure side, ChargePoint has added features to its fleet charging management software aimed at scheduling and load management to help control electricity costs.

Industry surveys and trade publications suggest fleet managers are placing greater emphasis on data and operational visibility as EV programmes move beyond pilot stages. The shift reflects a broader move towards software-led decision-making, as operators seek consistent information across vehicles, chargers and routes rather than relying on manual processes.

Operators using analytics-driven systems report higher vehicle availability, more predictable operating costs and better use of charging infrastructure. Predictive maintenance tools can flag potential issues earlier, reducing unplanned downtime that can disrupt delivery schedules.

Challenges remain, including integrating data from multiple vehicle manufacturers and addressing data security concerns. Even so, many fleet operators view these obstacles as manageable given the increased visibility and control provided by analytics platforms.

As electric fleets expand across the US, AI and analytics are expected to play a larger supporting role. While not a substitute for operational experience, the tools are becoming a core part of how commercial fleets manage the transition to electric vehicles.