Watch Now: LHP + SRES AI & Safety Webinar Series (Parts 1-3)
SRES partnered with LHP Engineering Solutions to host a free, 3-part webinar series exploring how the automotive industry can bridge the growing demands of AI, functional safety, and evolving standards. You can now watch all sessions on-demand below. Each part includes insights from Jody Nelson (Managing Partner at SRES) and Steve Neemeh (CTO at LHP), covering both technical guidance and strategic frameworks for responsible innovation.
Part 1 – Navigating the Future: Emerging Trends in Automotive Software and Evolving Standards
Software engineers are at the forefront of integrating smart, connected, and autonomous technologies into vehicle systems—all while facing intense pressure to reduce time-to-market and development costs. In this session, Jody Nelson (SRES) and Steve Neemeh (LHP) explore the evolving landscape of AI, open source, and cloud technologies in safety-critical automotive systems. They discuss the challenges of balancing business pressures with rigorous development practices, and share use cases that demonstrate how engineers are streamlining ISO 26262 compliance while maintaining high safety standards.
Part 2 – AI Risk Management in Action: ISO/IEC 42001 and ISO/PAS Requirements for Safer Development
With the introduction of the EU AI Act—the world’s first legal framework for regulating AI—organizations are now expected to manage AI risks proactively. This session explores how ISO/IEC 42001 provides a structured management system for AI, and how ISO/PAS 8800 supports validation and verification of AI systems in safety-critical development. Jody and Steve walk through a practical use case showing how AI can be used to generate system requirements, and how these practices can be integrated into existing ISO 26262 workflows.
Part 3 – Tying It All Together: A Roadmap for Advancing AI Development
This final part of the series outlines a clear path forward for teams looking to improve their AI development maturity. Jody and Steve focus on enabling AI governance through structured dataset lifecycles, adopting continuous verification and validation strategies, and building an ADS safety case aligned with ISO/TS 5083. They also highlight the tools and infrastructure needed to support AI-enabled features in production environments.
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