EV and software-defined vehicle engineering: the new operating model for automotive

When does the vehicle stop being the product? The moment software becomes the primary source of its value.

As our experts predicted, that inflection point is fast-approaching. The estimated value of the software-defined vehicle market is set to reach $400-$600 billion by 2030,¹ and 75% of automotive executives already believe the software-defined experience will be the core of brand value by 2035.²

For original equipment manufacturers (OEMs) and Tier 1 and Tier 2 suppliers alike, the implications span engineering architecture, talent strategy, regulatory compliance and value capture across the full vehicle lifecycle.

Here’s what this shift to software-defined vehicles (SDVs) means in practice and how leading institutions are responding.

why the SDV architecture shift is permanent, and what it means for OEMs and Tier 1 suppliers.

Just as smartphones shifted value from hardware to software, the automotive industry is undergoing the same migration, only with higher safety stakes and far more regulatory complexity.

For decades, vehicles were built around distributed networks of electronic control units (ECUs), each governing a single function. These ECUs were typically sourced from different suppliers and ran proprietary firmware. In 2023, one major OEM publicly acknowledged managing software written by different companies across a single vehicle, written in 100+ programming languages, with minimal interoperability between them.³

This model works when software is the secondary layer. But as software becomes the primary source of vehicle differentiation, the old ECU architecture becomes a constraint on development speed and scalability. A system built around independent, function-specific units can’t support the continuous, cross-domain logic that modern vehicles require.

The industry response is to centralize. OEMs are replacing fragmented ECU networks with zone-based architectures where software and hardware operate on independent update cycles. That decoupling is what makes OTA deployment, continuous integration and fleet-wide validation possible at scale.

The shift is already measurable:

By 2030, 81% of OEM fleets are expected to be software-defined, with over 90% of surveyed executives actively investing in the transition.⁴
The global automotive software and electronics market is projected to reach $519 billion by 2035, growing at a 4.5% CAGR, far outpacing overall vehicle market growth of around 1%.⁵
OTA updates have transformed vehicle ownership into a continuous software relationship where capabilities improve long after purchase.

As OEMs take direct control of the software layer, Tier 1 suppliers are feeling the pressure. Margins are compressing as OEMs disaggregate sourcing, build in-house software capabilities and reduce dependency on integrated system suppliers.

SDV compliance: how regulatory standards are reshaping engineering.

Regulatory standards now mandate specific engineering choices during the earliest stages of vehicle development, often before a single line of production code ships. The table below outlines the major frameworks and what they require from engineering teams.

where connected vehicle integration programs lose time and budget.

Integration is one of the most challenging aspects of SDV programs. Factory floor systems, embedded software and cloud platforms are often developed independently, with different data models and engineering assumptions. Connecting these layers without losing requirements traceability or introducing safety risk requires strong architectural discipline across the full program.

A key enabler is the digital thread: a continuous, traceable flow of data from requirements through design and real-world performance. Without it, a software change that clears simulation may surface a risk only in the vehicle, where it’s most expensive to address.

Three capabilities determine whether integration accelerates a program or compounds its risks:

Requirements traceability across domains, often enabled through Model-Based Systems Engineering (MBSE), to detect inconsistencies early and support safety certification.
AI-accelerated workflows for simulation, automated test generation and defect detection, alongside validation requirements under ISO 26262 and SOTIF.
Secure OTA and firmware over-the-air (FOTA) infrastructure for continuous software delivery and over-the-air firmware updates across the vehicle lifecycle.

Getting these right has a measurable impact. See how Randstad Digital helped one global automaker cut integration costs by 30% while scaling across 10 connected vehicle platforms.

conclusion.

The SDV transition cuts across engineering architecture, talent strategy, compliance and the full vehicle lifecycle simultaneously, with the need for specific expertise and execution across:

Functional safety: AUTOSAR and safety-critical C++ or Rust.
Cybersecurity: Designing and governing systems to UN R155 requirements from the earliest program phase.
AI and ML validation: Certifying probabilistic systems under ISO 26262 and SOTIF.
Connected vehicle platforms: Bridging OTA infrastructure, data pipelines and service layers across embedded and cloud environments.

Randstad Digital brings together automotive engineering expertise and next-generation digital capability to help OEMs and suppliers build faster, comply earlier and capture the revenue the SDV transition is creating. If your next SDV program is scaling, stalling or still being scoped, talk to our team today.

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