TomTom now covers more than two million EV charging points globally and plans to ship an AI-based battery range prediction model by the end of 2026 through a revised API, according to the company. The figures come from a TomTom newsroom update in which Drew Meehan, who leads the company’s Destination and Waypoint Management product group, reviews progress against the EV roadmap TomTom published two years ago. The company says it has since overhauled its charging point-of-interest (POI) data, added availability profiles and live pricing for stations, and unified its search and routing stack for EV-specific navigation.
Highlights
- TomTom’s EV charger POI coverage now exceeds two million chargers, with representation across North America, Europe, Southeast Asia and Korea.
- Charging-station availability profiles are built from six weeks of rolling usage data, using the same methodology TomTom applies to historic traffic flow.
- An AI-based range prediction model, replacing multi-variate equations, is on track to arrive by the end of the year as part of a new API.
- TomTom reports that EVs (BEV and PHEV) account for close to 30% of new-car sales across Europe on average, with Norway above 97%.
What TomTom Delivered Against Its 2024 EV Roadmap
Over the past two years, TomTom reports it has rebuilt its EV charging POI data, introduced more granular driver preferences for routing and charging, and launched availability profiles and live pricing for charging stations. A user feedback mechanism for correcting charger data is in development, and charger ratings and reviews are due soon.
“We had this EV vision that we created then made public two years ago. And we’ve done the things we said we would do,” Meehan said. “We added all these new preferences and functionalities to our EV products to help drivers charge when and where they want. And we’re still going, adding ratings and reviews [for chargers] very soon.”
TomTom attributes its coverage growth to what Meehan calls a “super aggregator” model: working with regional data partners rather than connecting to every charge point operator individually. The company says this approach lets it extend coverage into new markets more quickly.
According to Meehan, “In the places that matter most to our customers, we’re often better than the competition. Across the whole world, I would feel confident saying that the global leaders in EV POI data are now at parity with each other, TomTom included.”
How Availability Profiles Work
Beyond raw coverage, TomTom is emphasizing data depth. Availability profiles draw on six weeks of rolling usage data, applying the methodology the company uses for historic traffic flow, to show drivers how busy a charging point is likely to be at their expected arrival time. Reliability scoring, amenity information and pricing round out the station data.
The company positions these layers as the foundation of an EV navigation experience that works with or without advance planning. The approach builds on the EV routing and charging-stop capabilities TomTom co-developed with CARIAD for Volkswagen Group’s next-generation navigation system.
Charging Data Team Takes on Broader In-Car Services
Meehan’s group, previously focused on EVs, has been reorganized as Destination and Waypoint Management. Its scope now spans EV charging, POI search, fuel and charging prices, parking, in-car transactions and integration into TomTom’s AI platforms, including TomTom AI Assistant and its agent-based products.
TomTom frames EVs as a proving ground for software-defined vehicle features. Charger selection, amenity search, in-car payments, multi-stop routing and unplanned-stop support were built for electric driving, and the company says the underlying tooling now extends across vehicle types and use cases.
What Do EV Drivers Want From Charging Data Now?
TomTom says driver demand has shifted from finding a charger to choosing one. Drivers now ask for prices, payment integration, nearby amenities, security lighting and covered parking, according to the company.
“Now that we’ve satisfied that base level expectation; drivers are now applying personal preferences over simply finding a place to charge,” Meehan said. “They’re choosing a lower price. They’re choosing stops where they can get a coffee or eat or go to the toilet. They’re looking for stops that have WiFi, or where there are lights over the chargers for their personal safety. They’re asking for chargers that have overhead cover when it’s raining. Providing the location context to address these requests are the new challenges that we face.”
Meehan also expects vehicle-to-grid and vehicle-to-load functions to grow in importance, with the caveat that the driver experience must be reliable. TomTom’s example: a driver who wakes to find the car at 15% charge before a long trip because it fed the grid overnight will not use the feature again.
The company also flags slow charging, at home or at work, as lagging fast-charging infrastructure. TomTom’s position is that full EV adoption depends on slow charging becoming accessible and easily managed for everyone, with infrastructure improvement required alongside in-vehicle software. The EV Report recently covered GM’s breakdown of home charging options and costs for U.S. owners.
AI Range Prediction and a Background Intelligence Layer
TomTom’s next step is an AI-based service that learns a driver’s habits, anticipates charging needs and manages the vehicle day to day, adjusting for unexpected trips and detours. The company distinguishes this background intelligence layer from TomTom AI Assistant, which handles conversational prompts such as navigation queries and charging requests.
Meehan’s example scenarios include ensuring the car is charged before a habitual 8 a.m. commute, charging from solar on a day the driver typically does not drive, and keeping the vehicle fully charged during a calendar-flagged vacation week.
“There will always be a level of manual override to everything that we’re doing, and drivers should always have that option,” Meehan said.
The range prediction upgrade moves from multi-variate equations to learning models trained on actual usage data, accounting for weather, roof boxes, towing, tire pressure, open windows and driving style. TomTom says the update is on track for release by the end of the year in a new and revised API.
“EV has this natural complexity that we want to reduce,” Meehan said. “And we see that using some AI, some reasoning logic, our data, we can further reduce that cognitive load.”
