The $4 trillion shift to software-defined vehicles

Edward Wilford
Senior Research Director, Automotive

Maite Bezerra
Senior Principal Analyst,
Automotive: Software-Defined Vehicles

What is software-defined transformation in automotive?

The automotive industry is experiencing perhaps its most substantial transformation in the past century. Omdia estimates over $4 trillion in revenue will transition from traditional hardware-centric vehicles to software-defined vehicles (SDVs) between 2026 and 2037. This represents a fundamental shift from fixed-feature vehicles requiring physical recalls to dynamic platforms capable of continuous evolution through software updates.

Omdia analysts have proposed a specific SDV maturity framework to determine how this software-defined transformation progresses through five distinct levels.

At the foundation (Level 0-1), vehicles operate as software-enabled or connected products with fixed features and over-the-air (OTA) updates limited to firmware and security patches.

The market is projected to cross the SDV threshold in 2032, when SDV revenues ($2.59 trillion) will exceed the combined revenues of non-SDV and semi-SDV architectures ($1.3 trillion). Currently, traditional non-SDV vehicles (Level 0-1) represent 52% of the market in 2026, but this will decline sharply to just 6% by 2037.

Semi-SDVs (Level 2) introduce OTA upgrades (new functions) but are limited to the infotainment domain.

True SDVs emerge at Level 3 (upgradeable vehicles with continuous software evolution), advance to Level 4 (unified software platforms with hardware-software decoupling), and culminate in Level 5 (agentic orchestrators with AI-driven ecosystem integration).

The technology layers enabling SDV transformation

The foundation of SDV transformation rests on electrical/electronic (E/E) architecture evolution. Traditional distributed architectures, where individual electronic control units (ECUs) handle specific functions, are giving way to consolidated approaches. The progression moves from domain-centralized architectures through hybrid zonal to full zonal architectures, and ultimately to zonal-central compute systems.

Zonal-central compute architectures represent the pinnacle of hardware abstraction, enabling true hardware-software decoupling. The value of this decoupling of hardware and software is twofold. First, many hardware functions can be virtualized in software and are therefore not restricted to a single piece of hardware or need to be rewritten when transferred to alternative hardware. The second major advantage is that the software can be developed, simulated, and tested in the cloud in parallel to the development of system-on-chips (SOCs), which significantly reduces development time.

In China alone, these zonal architectures are expected to grow from near-zero to 14.9 million units by 2037, while North America is projected to lag at just 12% adoption.

This architectural shift enables dramatic cost reduction through fewer software variants and enhanced flexibility for future innovations. However, successful implementation demands advanced thermal management systems, high-speed and high-bandwidth deterministic in-vehicle connectivity networks spanning the entire vehicle, and robust separation of mixed-criticality workflows to ensure safety and performance integrity.

The Omdia 2026 SDV survey reveals that supporting technologies for these advanced architectures are at varying maturity stages. While Ethernet Time-Sensitive Networking (TSN), critical for deterministic connectivity, has achieved 30% implementation with 44% planning deployment by 2026-2027, other essential technologies lag. Hypervisors and virtual machines stand at 22% implementation, and containerized applications have reached only 24% adoption. 

Hardware abstraction and architectural evolution

Service-oriented architecture (SOA) emerges as a critical enabler, with 43% of respondents in the Omdia 2026 SDV survey having already implemented it; the highest deployment rate among technical SDV enabling capabilities. SOA provides standardized interfaces that allow different software components to communicate seamlessly, enabling cross-domain upgrades and modular software contribution.

Standardized APIs create the foundation for open ecosystem orchestration, allowing third-party applications and services to integrate with vehicle platforms. This open ecosystem is empowered by the cloud development environment that allows both global real-time development and a secure environment for third-party partners.

This capability becomes increasingly critical as vehicles evolve from closed systems to platforms supporting rapid integration of non-OEM voice assistants, driver assistance tools, and entertainment applications.

Despite these advantages, API standardization remains a significant industry challenge. The same Omdia survey reveals that 24% of respondents identify fragmentation of APIs, data formats, and protocols as a major barrier to scaling SDV implementations. This fragmentation creates integration complexity, increases development costs, and hinders the seamless interoperability that SOA promises to deliver.

The survey further reveals that software complexity and integration challenges concern 30% of respondents, while cybersecurity and safety concerns top the list at 33%. These challenges underscore the delicate balance required: SOA must provide the flexible framework necessary to accommodate an expanding ecosystem without compromising vehicle integrity, user experience, or safety-critical functions.

APIs and service-oriented architecture

The rapidly increasing capability of system-on-chips (SoCs) used in consolidated E/E architectures enables a shift toward edge computing in vehicles, allowing real-time processing of sensor data, reducing latency for safety-critical functions and minimizing dependence on cloud connectivity. Moreover, cross-domain AI orchestration and federated learning capabilities enable vehicles to learn from collective experiences, continuously improving performance across entire fleets while maintaining individual privacy and security.

Edge compute and AI integration

These edge computing and AI capabilities are paramount for several modern vehicle applications, including advanced driver assistance systems (ADAS), and autonomous driving capabilities require sophisticated AI platforms capable of processing vast amounts of data locally.

In the Omdia SDV survey, AI governance and AI safety runtime systems were recognized as essential by over 60% of industry professionals, yet none of these technologies are expected to become common practice until 2030 or later. This timeline underscores the complexity of deploying AI systems that meet stringent automotive safety standards and regulatory requirements.

Cross-industry convergence trends

This convergence extends beyond supplier relationships to encompass integration with smart city infrastructure, smart grid, IoT ecosystems, and mobility services. Vehicles are transitioning from standalone products to nodes in broader digital ecosystems, with 35% of survey respondents identifying ecosystem integration as a defining characteristic of advanced SDV maturity.

This convergence also creates new threat vector dynamics from a cybersecurity perspective. Interconnected nodes mean that cybersecurity has to be designed in from the initial design and that the system needs to be continuously monitored and updated throughout the life of the vehicle or any other interconnected node in the network. Increasingly, digital twins are becoming an essential part of the SDV operating reality, and this is a lesson other industries will need to learn.

Market dynamics: Competition and barriers to entry

The competitive landscape is splitting into two distinct models. Disruptor OEMs demonstrate a six- to seven-year maturity advantage over incumbents, with Omdia's forecast showing 88% will reach SDV Level 5 by 2037, compared to just 13% for incumbents.

However, incumbent OEMs leverage manufacturing scale and global experience to overtake disruptors in absolute SDV volume by 2031. By 2037, incumbents are projected to reach 51 million SDV units compared to disruptors' 16.5 million, demonstrating that volume can compensate for slower learning cycles.

The competitive bifurcation

China's dominance in SDV deployment is expected to moderate as the technology matures. Omdia predicts China's share of global SDV volume will decline from 77% in 2026 to 34% by 2037, representing a geographic rebalancing as Europe, North America, and Asia & Oceania accelerate adoption. This shift creates opportunities for automakers that can expand beyond China-centric strategies to capture $2.6 trillion in non-China SDV revenues by 2037.

The path forward requires incumbent OEMs to accelerate their transition to SDV Level 4—where investments finally justify ROI—establish clear roadmaps to exit semi-SDV architectures by 2030 and develop dual-track platform strategies that fund transformation while sustaining legacy business operations. Success depends on organizational transformation advancing in lockstep with technical deployment, a challenge that will define competitive positioning for the next decade and determine which traditional automakers successfully navigate the industry's most profound technological shift.

Currently, 89% of OEMs surveyed recognize that collaborative organizational structures are essential to SDV success, yet only 4% have implemented them—an 85-point recognition-to-implementation gap. While technical capabilities average 21% implementation, organizational capabilities lag at just 12%, representing the industry's true transformation challenge.

Organizational transformation challenge

Geographic rebalancing

SDV revenues will exceed non-SDV revenues in 2032 ($2.59tn vs. $1.3tn), while traditional vehicles decline from 52% to 6% market share by 2037. Exit semi-SDV architectures by 2030 and reach level 4 where investments justify ROI, or risk missing the $2.6 tn non-China opportunity.
89% of OEMs recognize collaborative structures are essential, yet only 4% have implemented them (technical capabilities: 21% vs. organizational: 12%). Organizational transformation must advance in lockstep with technical deployment to win.

As vehicles become ecosystem nodes, standardized APIs, cybersecurity, digital twins, and continuous monitoring become essential. Design these capabilities from development through vehicle lifecycle.
China's 77% market share (2026) will moderate to 34% by 2037. Disruptors lead in maturity (88% vs. 13% reaching level 5), but incumbents can leverage scale to overtake in volume by 2031. Develop dual-track strategies funding transformation while sustaining legacy operations and expand beyond China.

Maite Bezerra
Senior Principal Analyst,
Automotive: Software-Defined Vehicles

The bottom line

Edward Wilford
Senior Research Director,
Automotive

This research referenced is from:

Digital Mobility Intelligence Service