Underestimation of Software Complexity in Automotive

The automotive industry is moving toward software-defined vehicles (SDVs), which makes software central to how vehicles are designed, function, and are maintained over their lifecycle. But the industry’s hardware-centric roots mean software’s real challenges are still often underestimated. This shows up in how companies are organized, how they develop products, and how they allocate resources; hindering SDVs from reaching their full potential.

Below, we look at where this underestimation comes from, how it affects engineering and operations, and the strategic overhauls needed to align with a software-driven future.

Why Software Complexity Gets Underestimated

Automotive has been shaped by decades of mechanical and electrical engineering dominance. As a result, software has traditionally been treated as a supporting tool rather than a core competency, and with that its complexity structurally undervalued. This mindset persists even though modern vehicles now run huge amounts of code, on a scale that rivals aerospace systems, but with tighter real-time constraints and more integration points.

Engineers used to working with physical hardware prototypes often underestimate how abstract and iterative software development really is. Problems like dependency management, scalability, and cybersecurity scale up fast, and traditional engineering methods don’t handle them well.

The effects show up as longer development cycles: software bugs and integration problems, often rooted in fragmented legacy systems, cause significant delays. The industry’s hesitation to fully adopt agile practices makes this worse, as waterfall-style processes can’t keep pace with how SDVs need to evolve. This hesitation drives up costs and causes missed market windows. As AI and connectivity features multiply, the gap grows further: software has to manage more data flows, over-the-air updates, and regulatory requirements, while resources still skew toward hardware.

Consequences: Barriers to SDV Realization and Innovation

This underestimation ripples through the whole SDV ecosystem. Mismatched hardware-software interfaces and siloed teams create integration headaches, which drive up costs and slow innovation. For instance, regulatory delays and cybersecurity vulnerabilities arise when software risks are downplayed, leading to recalls and eroded consumer trust in autonomous features.

Traditional OEMs risk falling behind more software-native competitors if they don’t treat software as a genuine differentiator. Market forecasts point to strong growth in software and electronics segments — but only for companies that build the right capabilities; others risk stumbling through the transition.

The underestimation also weakens supplier collaboration and product management: under-resourced software teams struggle to keep up with the shift SDVs demand such as new business models like subscriptions and data-driven services. The result is a slower pace of adoption potentially ceding market share to those who prioritize software maturity.

Pathways Forward: Addressing the Gap Through Transformation

Fixing the underestimation of software complexity requires a phased, organization-wide transformation; starting with raising awareness, then moving toward embedded agile practices and cross-functional teams.

Key steps include:

• Introduce software as a distinct block in their V-Model with defined interfaces to allow agility in sw dev, separating sw from hw frequency
• Separating budgets and life cycle for sw from hw
• Introducing fast feedback loops between suppliers and OEM

For organization-specific roadmaps, contact us to tailor these transformations to your context.

Author: Hendrik Jilderda (hjilderda@knowmadmood.de)