)
Is AI actually good for business? Once you cut through the buzz and look at how its implementation translates into customer value, is this tech delivering on its lofty promises? For TomTom, the answer is a resounding yes.
It all comes down to strategy, mindset, high-quality data — and decades of experience with earlier iterations of AI-powered tech. As Ferenc Szeli, TomTom’s Head of AI, puts it, “AI is not new. It’s been around for over twenty years. TomTom is even older, and it’s nice to see how these two entities have grown together.” Ferenc says that mapping the world is a humongous task, and notes that right from the outset, AI has been an essential ingredient in augmenting mapmaking efforts. “We went from enriching our map content by capturing images and translating them to map features, automating a lot of our processes, introducing machine learning to make sure that our algorithms are up to date.” The demands of mapmaking have kept TomTom at the forefront of this technology for years — including the latest breakthroughs in generative and agentic AI.Watch: TomTom's Head of AI lays out the global mapmaker's AI strategy
AI as a mindset
Evolving in step with intelligent tech gave TomTom the edge: this new frontier was familiar territory, and the mapmaker quickly developed a sound strategy for figuring out how to make the most of it. The masterminds behind this approach frame AI not as a tool, but as a mindset — a new way of approaching challenges. The most obvious outcome of this is workforce efficiency. “By automating the menial, our highly trained specialist workforce can focus on the next level of value for customers.”
Ferenc doesn’t see AI in itself as a superpower. He sees it as a magnifier, one that turns your strengths into superpowers. But it can also magnify your shortcomings, so applying this mindset requires a keen sense of self-awareness. That’s why exploration is another important aspect; Ferenc has created an environment where TomTom employees can assess the viability of AI in a safe, controlled manner. “My team puts up the guardrails, set down the rules — making sure that people can focus on creating value instead of worrying about red tape.”Mapping what's possible
This strategy is already yielding results across TomTom’s suite of services and products. Right now, partners and customers around the world are feeling improvements firsthand, from map quality and accuracy to intuitive user experiences.TomTom Orbis Maps: AI inaccuracy, or ‘hallucinations’, present a big problem to the industry — but not to TomTom. In fact, advanced algorithms are speeding up the validation process of mapmaking, meaning TomTom’s maps reflect the real world faster and more accurately than ever before. And it comes down to the quality of data.
Maps are only as good as the data they’re built with, which is why TomTom sets an incredibly high standard for the data that makes its way into its partners’ products and its customers’ hands. Not only does TomTom curate data from various sources to cross-reference and validate viability, but these sources are also reputable and world-class — which, in short, means there’s no misinformation sneaking into TomTom datasets, and no hallucinations.
LiDAR captures data as millions of individual points that can be constructed into a three-dimensional image of the world. By combining this with live data and other sources, TomTom is able to automate lane-level-accurate mapping.Orbis for Automation: Mapping 3D road geometry down to the exact lane is a crucial element in automated driving. Normally, this is an expensive, labor-intensive task. But by combining detailed geographical data derived from cameras and LiDAR sensors on TomTom's mobile mapping (MoMa) vehicles with other data sources, such as live traffic, TomTom was able to automate this process, creating 3D maps with lane-level precision at unparalleled speed and scale. And this is where that AI mindset comes into play, as human experts still intervene at intersections — the most complex part of the map — along with general validation processes, to ensure a high standard of accuracy at every turn.
[Read more here: A new dimension for ADAS maps: TomTom Orbis Maps 3D]
TomTom AI Agent: In-vehicle voice guidance built with agentic AI is no doubt useful — but what sets TomTom AI Agent apart is the information it has access to. Built on multi-agent architecture, it connects with live traffic data, making it context aware — able to recognize and respond to the complexities of navigation — which Ferenc considers a true game changer. “A voice-based interaction is a lot more fluent, but most importantly, it's a lot more information dense. When you're on the road, you’re able to stay focused while accessing richer, timelier, more complex data.”
[Read more here: Why are carmakers racing to build smarter in-car AI?]
TomTom MCP Server: Navigation and routing is just one example of what agentic AI can do with TomTom’s datasets. To make it readily available for other applications (and other agents), TomTom introduced its Model Context Protocol (MCP) Server — an integration tool that allows your AI agent to connect to TomTom APIs and data. There’s no overstating how incredible this is: with TomTom’s MCP server, accessing and interpreting massive, complex, world-spanning datasets is now as easy as phrasing a request or question.
[Read more here: Connecting to the world of AI agents: Introducing TomTom Model Context Protocol Server]
Fixing bugs: Ferenc explains how optimizing internal processes, such as resolving customer-reported issues, is leading to faster product improvements: “One recent AI-tooling success was the bug triage tool. Finding the right teams or individual to address certain problems becomes increasingly complex as the organizational complexity grows. We set out to make sure that the very precious feedback we get from our customers and our partners — whether product gaps or bugs — is addressed as early and as effectively as possible. We trained an agent that was able to assign the tickets to the right teams with near-perfect accuracy.”
Not only does this save engineers time and energy — giving them space for pursuits beyond bug fixes — but it also translates to better customer experiences, as once problems are reported, they're quickly resolved.
By simply voicing a request, drivers can access complex navigation information via TomTom AI Agent.An intelligent approach
These are just some examples of TomTom’s recent successes. AI is foundational, its applicability across the organization wide-reaching. So, as this technology evolves and diverges into specialized areas, how does a business with such a broad portfolio stay up to speed with the latest tools? Ferenc has established a habit of endless discovery — encouraging people across TomTom to test new tech. “The ultimate goal of this is institutional learning,” he says. “You have to document your findings, make sure that the next person crossing the same bridge is armed with your knowledge and experience. Because these tools will keep leapfrogging each other, and we want to avoid being married to one tool — because there is no one tool to rule them all. We also need to differentiate across our portfolio and technology stack. So, this is a process of natural selection, ensuring that the ideas that generate the most value survive.” “This sandbox for internal-facing improvements means that we can really apply our best learnings and our best capabilities to the tech used by our partners and customers. And when the machine is well-trained, when our models are correct, our success becomes repeatable, it becomes predictable.”Curiosity and judgment
It’s a winning formula. By investing in people, encouraging exploration while remaining disciplined — with clear guardrails to keep potential applicability measurable and scalable — TomTom is getting real value out of AI. It’s a strategy that, coupled with decades-long expertise and rich, rigorously validated, reputably sourced data, lays the foundation for even greater results. Ferenc puts it best. “AI’s capabilities put a surplus on two human values that I deeply appreciate: curiosity and judgment. When you match your curiosity with judgment using AI capabilities, you create magic.”People also read
)
Why are carmakers racing to build smarter in-car AI?
)
Making maps at scale with AI and machine learning
)
Connecting to the world of AI agents: Introducing TomTom Model Context Protocol Server
)
Mapping road risks: How AI and data are revolutionizing traffic safety
* Required field. By submitting your contact details to TomTom, you agree that we can contact you about marketing offers, newsletters, or to invite you to webinars and events. We could further personalize the content that you receive via cookies. You can unsubscribe at any time by the link included in our emails. Review our privacy policy. You can also browse our newsletter archive here.