Survey of 450 automotive development professionals finds early adoption of modern toolchains key to maintaining competitiveness and software quality in AI-driven vehicle development.
MINNEAPOLIS, March 10, 2026 – Perforce Software, the DevOps company for global teams seeking AI innovation at scale, announces the seventh release of the State of Automotive Software Development Report. Findings from 2026 show that AI is emerging as a key driver of innovation, vehicles are more software-defined, and automotive development teams are increasingly concerned about managing the quality of complex systems amid growing supply chain challenges and global economic impact on the auto industry.
Investment for Competitiveness Is Focused on Modernizing Tech Stack, Not Hiring
As the global economy had a major impact on 56% of survey respondents, maintaining industry competitiveness was the number one goal for 57% of automotive professionals in this year’s report. Yet, report findings show that organizations are facing fewer resources, leaner dev teams, less outsourcing, and a slowdown in new location openings around the globe. To combat this, 39% of automotive software teams are still focusing on maximizing existing resources and 38% on educating existing talent, but compared to the same responses last year, these areas both decreased. The key strategy for 2026 may lie in teams’ increasing interest in modernizing their tech stacks, up from 30% to 33% this year.
The Race to Mitigate AI Risk and Maintain Momentum
Automotive manufacturers and suppliers are adopting AI at an unprecedented pace. This year, 71% said that they are using AI in their product design, and 45% are using it not just in development as a tool or assistant but also as a part of the end product.
This uptick in AI enthusiasm is tempered by respondents’ concerns about the safety (54%) and security (41%) of AI in vehicle development, largely because AI introduces a higher level of risk due to its non-deterministic behavior. The essential functional safety standard ISO 26262, autonomous vehicle guidance SOTIF 21448, and the recent ISO/PAS 8800 — which directly addresses the functional safety of AI in road vehicle development — are available to guide AI-driven development. However, compared to last year, fewer automotive development professionals said they are required to use ISO 26262 or SOTIF 21448, and there was decreased interest in adopting ISO/PAS 8800 despite the overall increase in AI use. More alarmingly, this year there are four percent fewer development teams using a coding standard at all. While seemingly small, even a four percent decrease in the use of a coding standard can have disastrous consequences for vehicle safety and security.
To help mitigate risk introduced by AI, modern lifecycle management and static analysis tools will be key to ensure continuous traceability and compliance with coding standards and functional safety standards. Emerging technology like AI-assisted code remediation, built into existing toolsets, will help teams remain agile by providing contextual fix suggestions for issues found. Since 55% already use static analysis/SAST tools to improve software quality, adopting these built-in features will continue to speed up automotive development.
Rust Steadily Grows as the Language of Choice for Safety-Critical Applications
Mitigating risk while boosting development velocity is also driving vehicle developers to change the way they code — not just using generative AI but expanding their programming language repertoire. While C, C++, and Python remain the top languages for automotive development in this year’s report, Rust use is slowly but steadily growing as the language of choice for safety-critical applications, from 9% in 2025 to 11% in 2026.
“Rust is particularly attractive to automotive and other safety-critical developers, because it replaces the rules and guidelines needed to write safe code in C and C++ with strong guarantees baked into the language itself,” said Alex Celeste, Principal Software Engineer at Perforce. “That means memory can’t be accessed incorrectly, after its lifetime or out of its bounds, except in clearly marked contexts, which radically improves safety by making correctness the default, not a special case that needs to be actively enforced for C and C++.”
Celeste, who is a member of the Safety-Critical Rust Consortium, explained that the consortium and other groups are working to deliver guidelines and standards that will help Rust fit into a safety-critical development pipeline, the lack of which has been a major barrier to adoption until now.
“We expect adoption of Rust to increase significantly once its limitation has been lifted,” she continued. “Several manufacturers are ready to progress from experiments to shipping products as soon as certification is possible.”
Now that over half (57%) of the survey respondents are deploying software defined vehicle (SDV) architectures, strategically applying modern development tools, best practices, and methodologies is already paying off. Recalls, for example, impacted five percent fewer survey respondents in 2026 (41% who were impacted) than in 2025 (46% who were impacted), despite Forbes reporting that automotive software recalls are on track to surpass previous recall numbers for the sixth year in a row. Newer technology, like the ability to perform over-the-air (OTA) updates, helps to triage full recalls and reduce costs, but it does not solve the root problems. As many of 55% of the survey respondents use a static analysis tool to help prevent software vulnerabilities as early as possible during development, which may account for the lower percentage of recalls in the Perforce report.
Other notable findings include:
- 53% identified managing complexity as the greatest quality concern — an increase of 25%.
- Of those who are developing SDVs, 81% consider electric vehicles (EVs) as part of their broader SDV strategy.
- 70% are using AI for SDV system optimization (e.g., predictive maintenance, in-vehicle personalization, and adaptive UI).
- 71% are implementing AI to some degree, but 54% are still concerned about safety in AI-driven vehicle development—specifically, safe decision-making for AI algorithms in autonomous vehicles.
- 82% are using at least one coding standard, which is important for code quality.
- 61% use MISRA® as the top coding standard — an increase of 8%.
- 36% still struggle with fulfilling safety requirements (and proving those requirements were met).
- 54% use Agile development as the proven process for developing quality software faster — an increase of 7%.
- Verifying and validating software continues to be the most time-consuming activities for automotive development teams (44%).
Maintaining the complexity of codebases and embedded automotive systems, now factoring in AI and software-driven vehicle development, highlights the need for modern, robust toolchains that can keep up with both emerging technologies and evolving standards. Organizations that are most able to adapt swiftly and modernize their tech stacks will be better positioned to weather the oncoming storms of market volatility.
The annual study, conducted in collaboration with Automotive IQ and the Eclipse Foundation, delivers exclusive research on the current challenges of developing safe and secure automotive software in increasingly complex, software-driven vehicles.
Interested parties can download the full 2026 State of Automotive Software Development Report by visiting: https://www.perforce.com/resources/sca/2026-state-automotive-software-development-report
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