Market Access and Compliance Innovation for Aibased Functional Safety Systems

The IEC Test Report Format (TRF) standardizes product testing and compliance, ensuring consistency across international standards and simplifying global certification. However, the increasing complexity of Artificial Intelligence (AI) and Functional Safety (FuSa) and Cybersecurity demands a more advanced and comprehensive approach. We introduce the Compliance Report Format (CRF)-an enhanced framework that builds upon IEC TRF by integrating AI assurance and FuSa compliance management. The CRF improves traceability, consistency, and efficiency in assurance case development and certification. To achieve this, the CRF incorporates key enhancements, including a profile-based approach, support for agile methodologies, explicit linkages to evidence, and integration with both the safety plan and assurance case. It also introduces structured arguments, synergy aspects, practical guidelines, and references to relevant research. With safety cases, a subset of assurance case, becoming increasingly central in UL 4600 “automotive autonomy” and the forthcoming IEC 61508 “generic Functional Safety (FuSa)” third edition, the CRF aligns with evolving regulatory landscapes. It also supports IOS/IEC TR 5469 “AI and FuSa”, strengthening the integration of AI and safety. By promoting a shift-left approach, the CRF facilitates early AI risk analysis, FuSa integration, and continuous validation, reducing late-stage compliance burdens. Additionally, by leveraging agile practices and the definition of ready concept, it minimizes compliance overhead while enhancing traceability of AI-related safety evidence. CRF's profile-based methodology tailors AI and FuSa requirements to domain-specific standards, ensuring flexibility and adaptability. Development engineers benefit from structured guidelines, references to industry standards, and links to scientific research, streamlining compliance efforts. By modernizing the compliance landscape, the CRF empowers engineers, auditors, and certification bodies to navigate AI-driven safety and cybersecurity challenges more effectively.