The rapid integration of artificial intelligence into automated and connected vehicles is reshaping the foundations of road transport, introducing unprecedented opportunities for safety enhancement while simultaneously exposing critical socio-technical risks. Contemporary vehicles are no longer isolated mechanical systems; they are complex cyber-physical entities embedded within extended digital ecosystems, regulated by evolving international standards and public policies. This research article develops a comprehensive, theoretically grounded analysis of how functional safety, cybersecurity, data governance, and regulatory oversight intersect in AI-enabled automated driving systems. Drawing strictly on established international standards, regulatory instruments, accident investigation reports, and peer-reviewed academic literature, the study explores how safety assurance practices are transitioning from traditional quality management approaches toward risk-based, system-of-systems governance models capable of addressing machine learning uncertainty, human–machine interaction complexity, and extended vehicle architectures. The methodology adopts an integrative qualitative research approach, synthesizing normative frameworks such as ISO 26262, ISO 20077, UN Regulation No. 155, and emerging European Union artificial intelligence legislation with empirical insights derived from safety incidents, regulatory assessments, and software engineering research. The findings demonstrate that safety in AI-driven mobility cannot be achieved through isolated compliance with individual standards; instead, it requires a harmonized governance architecture that aligns technical design, organizational safety culture, regulatory accountability, and transparent data practices. The discussion critically examines limitations of current frameworks, including residual ambiguity in responsibility allocation, challenges in validating adaptive AI behavior, and tensions between innovation and precaution. The article concludes by outlining future research and policy directions necessary to sustain public trust and ensure ethically aligned, resilient, and socially acceptable deployment of automated vehicle technologies.

Automated driving systems, artificial intelligence safety, functional safety, cybersecurity regulation

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