Investing for the AI Era: How Software-Defined Vehicles Are Reshaping Automotive Strategy
The Investing for the AI Era: How Artificial Intelligence Is Reshaping Car Manufacturingautomotive industry is entering a new phase in which software and artificial intelligence are becoming central to how vehicles are designed, developed and improved. As the software-defined vehicle (SDV) era accelerates, carmakers face a fundamental strategic question: which technologies should they develop internally, and where should they rely on specialist partners?
TheAI Era decisions being made today will influence how quickly automakers can innovate over the next decade. At the Future of the Car summit in London, TomTom Chief Product Officer Leo Sei highlighted how software-defined architecture decisions made now will establish the foundation for successive generations of AI-enabled vehicles.
For automakers, the challenge is not simply adopting new technology. It is determining where investment can create meaningful competitive differentiation and where partnering with specialists can provide greater speed, scale and access to expertise.
The Shift From Hardware to Software
Deciding what to build internally and what to source externally is not new to the automotive industry. Supply-chain resilience, manufacturing costs, technological complexity and specialist expertise have long influenced decisions about which components automakers should produce themselves.
Historically, greater ownership of the manufacturing process could provide greater control over the physical characteristics and driving experience of a vehicle. Hardware was often a primary source of differentiation.
The AI Era emergence of software-defined vehicles is changing that model.
Modern vehicles are increasingly becoming software platforms capable of receiving updates, incorporating new capabilities and evolving throughout their lifecycles. As a result, a vehicle’s value is no longer determined entirely at the moment it leaves the factory.
Instead, long-term value increasingly depends on what the vehicle can become through software, AI and continuous updates.
As AI Era Giovanni Giancaspro, Automotive Market Segment Manager, explains, the industry is moving toward software and AI architectures that can learn, evolve and improve across multiple vehicle generations.
That makes the strategic design of the SDV platform particularly important. Technologies that will eventually support advanced driver assistance and higher levels of automated driving depend on infrastructure decisions being made today.
Separating Foundation From Differentiation
One way to approach the SDV strategy is to divide the vehicle’s digital architecture into two broad layers: foundation and differentiation.
The AI Era foundation layer consists of the technologies that allow the vehicle’s digital ecosystem to operate. These can include silicon and compute, operating systems and middleware, cloud infrastructure, connectivity, over-the-air software delivery, cybersecurity, maps, location intelligence and core AI capabilities used to interpret the driving environment.
This layer is increasingly data-driven, continuously updated and designed to scale across multiple vehicle models and generations.
Above it sits the differentiation layer. This is where automakers can establish how their vehicles behave and feel, from driving characteristics and user interfaces to brand-specific digital services and customer experiences.
The AI Era distinction is important because not every part of an SDV platform creates the same level of competitive advantage.
Foundational technologies can require substantial investment to develop and maintain, while offering limited differentiation from one vehicle brand to another. As the complexity of these systems increases, specialist providers can potentially deliver foundational capabilities at greater scale.
That allows automakers to concentrate their resources on areas where their brand and product strategy can make a meaningful difference.
Specialization Becomes More Important
The growing complexity of vehicle software is increasing the value of specialized technology providers.
Some AI Era technologies are essential to the operation of an SDV but may not, by themselves, define the customer experience. Building every foundational component internally can therefore consume significant capital, engineering talent and development time.
Location intelligence provides one example.
Navigation was once primarily viewed as a feature displayed on the vehicle’s dashboard. Today, location technology can provide an environmental intelligence layer that helps vehicles understand the world around them.
For AI Era ADAS and automated driving, accurate location information can support the vehicle’s understanding of roads, lanes, intersections and other environmental conditions. That information can then be used by higher-level systems to make decisions and communicate relevant information to drivers and passengers.
TomTom describes this type of location intelligence as a continuously updated representation of reality that can serve as a foundation for increasingly sophisticated driving experiences.
The broader principle extends beyond automotive.
In cloud computing, for example, specialist providers build and operate foundational infrastructure such as data centers, compute, storage and networking. Software companies can then build differentiated products and services on top of that infrastructure without having to recreate every underlying component.
A similar model can apply to software-defined vehicles.
Investing Where Differentiation Matters
The strategic objective for automakers is therefore not necessarily to own every layer of the technology stack. Instead, it is to determine where ownership provides meaningful differentiation and where partnerships can accelerate development.
“The AI Era software-defined vehicle is happening today,” Sei emphasized at the Future of the Car summit.
For automakers, differentiation remains closely tied to the driving experience. That includes vehicle performance, handling, interfaces, displays, navigation, ergonomics and the way ADAS and automated-driving functions interact with the driver.
It also extends beyond the vehicle itself.
As Filip Klippel, Automotive Market Segment Manager, notes, a brand’s identity encompasses the broader customer relationship, including purchasing, ownership, maintenance and the sensory and digital experience associated with the vehicle.
This AI Era means automakers can potentially create greater value by directing resources toward the experiences customers directly associate with their brands.
“Customization is where carmakers keep their brand DNA,” Sei said. “You probably don’t want a Porsche and a Škoda to have the same automated driving experience — but that doesn’t mean you need to own the entire layer all the way down to the representation of the world.”
The underlying technology can therefore be shared while the customer-facing experience remains distinct.
Flexibility Is Key to Future SDV Platforms
There is no universal formula for determining which technologies an automaker should build internally and which it should source from partners.
The appropriate balance depends on each company’s strategy, capabilities, resources and priorities.
Flexible partnerships can help address this challenge by allowing automakers to adopt specialized technologies selectively. Modular solutions can provide access to specific capabilities without requiring an automaker to outsource its entire technology architecture.
This flexibility becomes particularly important as automated driving develops.
The AI Era underlying automated-driving system may be based on common foundational technologies, but the way those capabilities are presented and experienced can differ substantially between brands.
Location intelligence sits beneath these experiences by providing the contextual information automated-driving systems need to understand their surroundings. It can also help translate complex system decisions into information that drivers can understand quickly.
Building the Foundation for the AI-Defined Vehicle
TomTom’s Orbis platform illustrates how specialized foundational technology can support this model. Drawing on decades of location expertise, Orbis provides a continuously refreshed representation of the world using automated multi-source data fusion.
The AI Era platform is designed to provide lane-level location intelligence for navigation, ADAS and automated driving, creating a common foundation on which automakers can build differentiated vehicle experiences.
As vehicles become increasingly defined by software and AI, the strategic question is no longer simply what an automaker can build itself.
The more important question is where internal ownership creates meaningful value and where specialist partnerships can deliver better speed, scale and innovation.
The automotive industry is moving toward an AI-defined future in which vehicles will increasingly evolve throughout their lifecycles. Automakers that combine strong foundational technology with distinctive, continuously improving customer experiences will be positioned to respond to that change.
The AI Era goal is not to own every layer of the technology stack. It is to build the right foundation, preserve flexibility and invest deeply in the technologies and experiences that define the brand.
Source Link: https://www.tomtom.com/