As the connected-car ecosystem evolves, it will affect multiple value chains, including those for automotive, telecommunications, software, and semiconductors. In this report, we explore some of the most important changes transforming the sector, especially the opportunities that may arise from the growth of 5G and edge computing. We also examine the value that semiconductor companies might capture in the years ahead if they are willing to take a new look at their products, capabilities, organizational and operational capabilities, and their go-to-market approaches.

A new age of vehicle software and electronics

Four well-known technology trends have emerged as key drivers of innovation in the automotive industry: autonomous driving, connectivity, electrification, and shared mobility—such as car-sharing services (Exhibit 1). Collectively, these are referred to as the ACES trends, and they will have a significant impact on computing and mobile-network requirements. Autonomous driving may have the greatest effect, since it necessitates higher onboard-computing power to analyze massive amounts of sensor data in real time. Other autonomous technologies, over-the-air (OTA) updates, and integration of third-party services will also require high-performance and intelligent connectivity within and outside of the car. Similarly, increasingly stringent vehicle safety requirements require faster, more reliable mobile networks with very low latencies.

With ACES functions, industry players now have three main choices for workload location: onboard the vehicle, cloud, and edge (Exhibit 2).

To ensure that use cases meet the thresholds for technical feasibility, companies must decide where and how to balance workloads across the available computing resources (Exhibit 3). This could allow use cases to meet increasingly strict safety requirements and deliver a better user experience. Multiple factors may need to be considered for balancing workloads across onboard, edge, and cloud computing, but four may be particularly important. The first is safety, since workloads essential for passenger safety require extremely fast reaction times. Other considerations include latency, computing complexity, and requirements for data transfer, which depend on the type, volume, and heterogeneity of data.

Connected-car use cases today typically rely on either onboard computing or the cloud to process their workloads. For example, navigation systems can tolerate relatively high latency and may function better in the cloud. OTA updates are typically delivered via a cloud data center and downloaded via Wi-Fi when it is least disruptive, and infotainment content originates in the cloud and is buffered onboard to give users a better experience. By contrast, accident prevention workloads such as autonomous emergency-braking systems (AEBS) require very low latency and high levels of computing capability, which, today, may mean that they are best processed onboard the vehicle.

Advances in computing and connectivity are expected to enable many new and advanced use cases (Exhibit 4). These developments could alter where workloads are located. Of particular significance, the rollout of 5G mobile networks could allow more edge processing. Given the importance of these interrelated technologies, we explored their characteristics in detail, focusing on automotive applications.

The benefits of 5G and edge computing

5G technology is expected to provide the bandwidth, low latency, reliability, and distributed capabilities that better address the needs of connected-car use cases. Its benefits to automotive applications fall into three main buckets:

• Enhanced mobile broadband (EMBB): 5G may provide faster, more uniform user experiences with speeds reaching ten gigabits per second, five to ten times faster than 4G technology. This may enhance high-bandwidth use cases such as in-car infotainment, vehicle teleoperation, and real-time human-machine-interface rendering.
• Massive Internet of Things (IoT): By enabling up to a million connections per square kilometer, 5G networks could efficiently support a large number of concurrent connections from cars on the road, connected infrastructure end points, and end-user devices. This may eliminate the possibility that cars and other devices get disconnected from the mobile network inadvertently because of a large number of connections.
• Ultra-low-latency communications (URLLC): 5G latency can theoretically go down to one millisecond—five to 15 times better than 4G. This means 5G can combine high speed with high reliability, eliminating the need for trade-offs between the two. This is important for object tracking in autonomous vehicles, the protection and control of smart-grid critical infrastructure, and remote-control and process automation for applications including aviation and robotics.

These benefits could contribute to greater use of edge applications within the automotive sector. Workloads that are not safety-critical—infotainment and smart traffic management, for example—could start to shift to the edge from onboard or in the cloud. Eventually, 5G connectivity could reduce latency to the point that certain safety-critical functions could begin to be augmented by the edge infrastructure, rather than relying solely on onboard systems.

Most current automotive applications today tend to rely exclusively on one workload location. In the future, they may use some combination of edge computing with onboard or cloud processing that delivers higher performance. For instance, smart traffic management systems may improve onboard decision making by augmenting the vehicle’s sensor data with external data (for example, other vehicles’ telemetry data, real-time traffic monitoring, maps, and camera images). Data could be stored in multiple locations and then fused by the traffic management software. The final safety-related decision will be made onboard the vehicle. Ultimately, large amounts of real-time and non-real-time data may need to be managed across vehicles, the edge infrastructure, and the cloud to enable advanced use cases. In consequence, data exchanges between the edge and the cloud must be seamless.

Shifting industry dynamics and new opportunities

The evolving automotive value chain will open many new opportunities for those within the industry and external technology players. The total value created by connected-car use cases could reach more than $550 billion by 2030, up from about $64 billion in 2020 (Exhibit 5).

Increased connectivity opens up opportunities for players across the automotive value chain to improve their operations and customer services. Take predictive maintenance in cars as an example. Aftermarket maintenance and repair provision now predominantly involve following a fixed interval maintenance schedule or reactive maintenance/repair. There is little visibility around the volume of vehicles that need to be serviced in a particular period, leading to inefficiencies in service scheduling, replacement parts ordering, and inventory, among others. Predictive maintenance using remote car diagnostics could improve the process by giving OEMs and dealers an opportunity to initiate and manage the maintenance process.

The pace of rollout of advanced connected-car use cases is highly contingent on the availability of 5G and edge computing. A variety of factors are converging to accelerate this. Demand is rising for these critical enablers, fueled by a proliferation of consumer and industry use cases. In the short term, value may be generated through enhancements to services already available with 4G, including navigation and routing, smart parking, centralized and adaptive traffic control, and monitoring of drivers, passengers, or packages.

We expect that greater 5G and edge availability may expand the list of viable use cases (technically and financially), boosting edge value exponentially. Looking to 2030, about 30 percent of our value estimate may be enabled by 5G and edge (from 5 percent in 2020), largely consistent with our cross-sectoral report on advanced connectivity.

Value creation could be accelerated by traditional players moving into adjacencies and by new entrants from industries not traditionally in the automotive value chain, such as communication system providers (CSPs), hyperscalers, and software developers. Players such as Intel, Nvidia, and the Taiwan Semiconductor Manufacturing Company are adding automotive-software capabilities, leading to greater synergies and vertical-integration benefits. In addition to accelerating value creation, new entrants may compete for a greater share of the total value.

Automotive-hardware value chains are expected to diverge based on the type of OEM. Traditional auto manufacturers, along with their value chains, are expected to see a continuation of well-established hardware development roles based on existing capabilities. Automobiles, components, devices, and chips for applications ranging from cars to the cloud may continue to be primarily manufactured by the companies that specialize in them. Nontraditional or up-and-coming automotive players could codevelop vehicle platforms with the established car OEMs and use OEMs’ services or contract manufacturers such as Magna Steyr for the traditional portions of the value chain.

Established players may seek to increase their share by expanding their core businesses, moving up the technology stack, or by growing their value chain footprints. For instance, it is within the core business of semiconductor players to create advanced chipsets for automotive OEMs, but they could also capture additional value by providing onboard and edge software systems or by offering software-centric solutions to automotive OEMs. Similarly, to capture additional value, hyperscalers could create end-user services, such as infotainment apps for automotive OEMs or software platforms for contract manufacturers.

Emerging ecosystem archetypes

As players make strategic moves to improve their position in the market, we can expect two types of player ecosystems to form. In a closed ecosystem, membership is restricted and proprietary standards may be defined by a single player, as is the case with Volkswagen, or by a group of OEMs. Open ecosystems, which any company can join, generally espouse a democratized set of global standards and an evolution toward a common technology stack. In extreme examples—where common interfaces and a truly open standard exist—each player may stay in its lane and focus on its core competencies.

Hybrid ecosystems will also exist. Players following this model are expected to use a mix of open and closed elements on a system-by-system basis. For example, this might be applied to systems in which OEMs and suppliers of a value chain have particular expertise or core competency.

Exhibit 6 describes the advantages and disadvantages of each ecosystem model.

Value chain dynamics

Companies in the emerging connected-car value chain develop offerings for five domains: roads and physical infrastructure, vehicles, network, edge, and cloud. For each domain, companies can provide software services, software platforms, or hardware (Exhibit 7).

As automotive connectivity advances, we expect a decoupling of hardware and software. This means that hardware and software can develop independently, and each has its own timeline and life cycle. This trend may encourage OEMs and suppliers to define technology standards jointly and could hasten innovation cycles and time to market. Large multinational semiconductor companies have shown that development time can be reduced by up to 40 percent through decoupling and parallelization of hardware and software development. Furthermore, the target architecture that supports this decoupling features a strong middleware layer, providing another opportunity for value creation in the semiconductor sector. This middleware layer may likely be composed of at least two interlinked domain operating systems that may handle the decoupling for their respective domains. Decoupling hardware and software, which is a key aspect of innovation in automotive, tilts the ability to differentiate offerings heavily in favor of software.

New opportunities. In the software layer, companies could obtain value in several different ways. With open ecosystems, participants will have broadly adopted interoperability standards with relatively common interfaces. In such cases, companies may remain within their traditional domains. For instance, semiconductor players may focus on producing chipsets for specific customers across the domains and stack layers, OEMs concentrate on car systems, and CSPs specialize in the connectivity layer and perhaps edge infrastructure. Similarly, hyperscalers may capture value in cloud/edge services.

In closed ecosystems, by contrast, companies may define proprietary standards and interfaces to ensure high levels of interoperability with the technologies of their members. For example, OEMs in a closed ecosystem may develop analytics, visualization capabilities, and edge or cloud applications exclusively for their own use, in addition to creating software services and platforms for vehicles. Sources of differentiation for vehicles could include infotainment features with plug-and-play capabilities, autonomous capabilities such as sensor fusion algorithms, and safety features.

While software is a key enabler for innovation, it introduces vulnerabilities that can have costly implications for OEMs, making cybersecurity a priority (see sidebar, “The importance of cybersecurity,” for more information). Combined, the 5G and edge infrastructure could potentially offer increased flexibility to manage security events related to prevention and response.

Hardware players could leverage their expertise to offer advanced software platforms and services. Nvidia, for instance, has entered the market for advanced driver-assistance systems (ADAS) and is complementing its system-on-a-chip AI design capabilities with a vast range of software offerings that cover the whole automated-driving stack—from OS and middleware to perception—and trajectory planning.

Some companies are also moving into different stack layers. Take Huawei, which has traditionally been a network equipment provider and producer of consumer-grade electrical and electronic (E&E) equipment, and manufacturer of infrastructure for the edge and cloud. Currently, the company is targeting various vehicle stack layers, including the base vehicle operating systems, E&E hardware, automotive-specific E&E, and software and EV platforms. In the future, Huawei may develop vehicles, monitoring sensors, human–machine interfaces, application layers, and software services and platforms for the edge and cloud domains.