Summary

• TomTom has announced three operating divisions, with approximately 200 roles affected.
• Third-quarter group revenue fell 6% to €129 million, while automotive operational revenue declined 19%.
• New AI-oriented integrations are intended to make the company's mapping data available to enterprise applications.

Dutch mapping technology company TomTom is reorganising around automated driving, location intelligence and navigation, with approximately 200 roles affected as management attempts to develop new commercial opportunities while addressing pressure on its automotive business.

The restructuring was announced with TomTom’s third-quarter results on 15 October. Group revenue declined 6% to €129 million, while automotive operational revenue fell 19%, providing a financial context for the company’s decision to reduce management layers and reorganise its activities.

The three divisions are intended to focus on distinct customer requirements. Automated Driving will concentrate on technology supporting vehicle automation, Location Intelligence will serve business applications, and Navigation will retain responsibility for products and services associated with conventional navigation systems.

Chief executive Mike Schoofs identified AI as an influence on the company’s prospects in automated driving and enterprise location intelligence. Management expects changes in how developers use geographical information to create opportunities beyond its established navigation market.

Those expectations sit alongside continuing pressure on automotive revenues. TomTom supplies mapping and navigation technology to vehicle manufacturers, whose development programmes, commercial arrangements and product cycles can affect demand independently of the wider market for location data.

Separating automated driving from navigation could allow the company to manage those differences more directly. However, organisational changes do not themselves establish that emerging AI services will generate sufficient revenue to offset weakness in established contracts.

Location data becomes available to AI agents

TomTom has expanded its relationship with Microsoft to make location intelligence accessible through applications developed using Microsoft Fabric and Microsoft Foundry. It has also introduced a Model Context Protocol server through Claude’s connector directory.

The latter allows compatible AI applications to call defined mapping capabilities using a structured interface, rather than requiring a person to move manually between a conversational system and a separate map or routing service.

Such integrations could support applications involving logistics, property analysis, route planning or asset management. A business application might combine operational information with location data to calculate routes, identify relevant facilities or place an event within a geographical context.

However, the existence of an interface does not establish that AI agents can execute every related business process reliably. Routing decisions may depend on live conditions, vehicle restrictions, delivery commitments and commercial priorities that extend beyond the information provided by a general mapping service.

Organisations also need to examine how an AI system identifies the data it uses, whether that information remains current and what permissions apply when a tool interacts with external services. Location data is useful partly because it can be combined with other operational records, but those combinations may introduce privacy and security requirements.

TomTom’s existing portfolio includes mapping, routing, traffic information and developer services. AI connectors offer another distribution channel for those capabilities, although the company has not published independently verified commercial results showing the additional revenue attributable to the new integrations.

The automated driving division faces a different problem. Vehicle systems require detailed and frequently updated information about road environments, while their operation must satisfy demanding safety and performance requirements.

AI techniques can contribute to the interpretation of road information and the development of mapping systems, but technical progress must be validated through the processes required for the intended vehicle functions.

Restructuring changes the cost base

TomTom says the organisational changes are intended to simplify management and bring decisions closer to development and commercial teams. Approximately 200 roles will be affected, although the company has not established that this figure represents confirmed redundancies in every case.

The reorganisation is expected to influence costs as well as the company’s operating structure. Management has raised its full-year operating margin outlook to 4%, with a higher figure of approximately 7% before the restructuring charge.

Those figures describe different financial measures. The higher margin must not be presented as the company’s reported margin or as evidence that the restructuring has already generated all its anticipated benefits.

TomTom’s financial performance remains tied to its ability to convert technical developments into revenue. Enterprise location services may reach customers through familiar software environments, but customers still need to determine whether the functionality delivers sufficient business value to justify licences, integration and ongoing usage costs.

Competitive pressure is also likely to shape the market. As more applications can call mapping services through standard interfaces, providers will need to distinguish themselves through data quality, coverage, update frequency, commercial terms and reliability.

Vehicle automation imposes separate costs associated with specialist engineering, testing and integration. The new divisional structure may allow TomTom to direct resources more closely towards those requirements, but it does not remove dependence on the pace at which vehicle manufacturers develop and commercialise automated systems.

Management expects improvement in Location Technology revenue during 2027, supported by the reorganised business and its product strategy. That remains a forward-looking expectation rather than a result demonstrated in the current quarter.

TomTom’s decision combines immediate financial discipline with longer-term attempts to expand the commercial use of its technology. The subsequent results will show whether gains from enterprise location intelligence and automated driving can compensate for the pressure visible in its established automotive operations.