Vehicles are learning to understand the world in a new way.
For decades, maps were primarily designed around the driver: helping people choose routes, plan journeys, and reach their destinations. In the age of intelligent vehicles, that role is expanding. Maps are increasingly becoming part of the vehicle's own intelligence system, helping vehicles interpret road structures, respond to changing conditions, support automated driving decisions, and make those decisions more understandable to the people inside the car.
In other words, the value of maps is no longer limited to navigation. They are becoming part of the foundational intelligence layer of the automobile.
For TomTom, a company with more than three decades of experience in mapping, navigation, and location technology, this shift is not about replacing its core capabilities. It is about seeing their value in a new light. As electrification, software-defined vehicles, automated driving, and AI converge in the automotive industry, vehicles need more than a growing list of advanced features. They need an intelligence layer that can translate road data, vehicle systems, and user needs into scalable solutions for global deployment.
In an interview with Gasgoo's C Talk, TomTom CEO Mike Schoofs did not frame maps simply as a navigation tool. He placed them in a broader context: automated driving, in-vehicle AI, partner ecosystems, and user experience.
From his perspective, TomTom sits at a critical point where several technology trends are converging. Automated driving needs data that is accurate, fresh, high-quality, and broad in coverage. In-vehicle AI and intelligent cockpits, meanwhile, need location context to translate seemingly simple user requests into executable in-car experiences. Maps are no longer static information displayed on a screen. They are becoming a dynamic foundation that intelligent vehicle systems continuously rely on.
That helps explain how TomTom's role has evolved in recent years. The company is not leaving the map business for an entirely different field. Rather, it is redefining what maps can mean in the era of AI-powered vehicles. Road Model, Lane Model, dynamic traffic data, hazard alerts, real-time road intelligence, and in-vehicle AI interaction are being built on top of map data, pushing TomTom from a traditional map supplier toward a broader location intelligence platform.
Automated driving is one of the clearest examples of this shift.
Mike noted that TomTom is supporting different levels of automated driving, starting from L2+. But for automated driving to gain real user acceptance, technical capability alone is not enough. Trust matters. Drivers and passengers need to understand what the vehicle is doing, why it is doing it, and what it is likely to do next. Location intelligence, therefore, must serve not only vehicle decision-making, but also human understanding.
This is also where intelligent vehicles differ fundamentally from traditional vehicles. A car is no longer just a mechanical means of transport. It is becoming, as Mike put it, a "computer on wheels." As E/E architectures, perception systems, software platforms, and AI capabilities continue to evolve, maps, ADAS, and in-vehicle AI can no longer be treated as separate domains. TomTom's "one map, one system" approach is aimed at reducing in-vehicle complexity through system-level integration, while embedding map capabilities more deeply into intelligent driving and in-car experiences.
AI is accelerating that transition.
On the map production side, TomTom is building Orbis Maps, particularly its Lane Model map, with an AI-first approach. The significance is not simply that maps are becoming more detailed. The more important question is whether lane-level map data can be created, updated, and scaled across different road classes and geographies in an automated and cost-efficient way. For automakers looking to deploy intelligent driving functions globally, that capability can determine whether a solution remains a one-off project or moves into large-scale production.
On the in-car interaction side, TomTom's AI agent, TAIA, points to another direction: location data is becoming part of a more natural user experience. A request such as finding a restaurant that serves vegetarian food, offers vehicle charging, and is compatible with a specific car model may sound simple to the user. But behind the scenes, it requires restaurant information, charging infrastructure, vehicle data, route planning, and real-time road intelligence to work together. TomTom is not trying to take over the vehicle's "brain." Its focus is on navigation and location-related scenarios, turning complex location intelligence into a smoother in-car experience.
If AI is expanding the boundaries of map capabilities, the Chinese market is reshaping how global suppliers need to respond.
In Mike' view, one of the most striking changes brought by Chinese automakers is the acceleration of development cycles and collaboration models. Some traditional automakers still work on three-year vehicle development timelines. Chinese automakers, especially those expanding overseas, are increasingly talking in terms of "months," not "years." That speed is not only changing the Chinese market; it is also putting pressure on other regions and automakers around the world to move faster.
For TomTom, China is not only a growth market. It is also a test of capability. Chinese customers expect innovation, fast execution, flexible collaboration, cost efficiency, and reliable quality at the same time. To keep pace, global suppliers cannot treat China merely as a sales market. They need local engineering resources, local management capabilities, and local ecosystem collaboration close to the customer.
This is why TomTom has continued to strengthen its Shanghai team and local engineering footprint. Over the past 24 months, the company has won a significant number of programs in China. In the first quarter of this year alone, TomTom and its partners delivered more than 100,000 vehicles outside China. Behind that figure is a closer link between the global expansion of Chinese automakers and the location intelligence capabilities needed to support them.
But speed is not the whole story.
When Chinese customers ask for better products, innovative solutions, flexible cooperation, faster delivery, and cost efficiency all at once, Mike' answer is clear: quality and user experience must come first. Ultimately, the value of any technology is not judged by suppliers or automakers, but by the end users who sit in the vehicle, buy it, and use it every day.
That also helps define TomTom's role as Chinese automakers move further into global markets. For Chinese brands going overseas, competition is no longer only about how quickly products can be launched. It is about whether intelligent driving functions, in-car experiences, and service capabilities can be reliably replicated across different markets. Road environments, regulations, user habits, and ecosystem partners vary from region to region. Automakers need more than a single map product; they need location intelligence that can support global deployment.
Seen from this perspective, TomTom is not simply facing another upgrade cycle in the mapping industry. It is participating in a broader reorganization of the automobile's foundational intelligence. Maps, data, AI, user experience, and global deployment capabilities are being reassembled, and TomTom is positioning itself as both a connector and a scale enabler in that process.
In this interview, Mike Schoofs discussed TomTom's new chapter, the evolution of maps and location intelligence, its AI applications, changes in the Chinese market, the global expansion of Chinese automakers, and the company's global partnership cases.
