Abstract: Vehicle passive safety performance serves as the final protective barrier for the lives of drivers and passengers. Traditional development models suffer from issues such as long cycles, high costs, and limited scenario coverage. However, Artificial Intelligence (AI) technology, leveraging its powerful capabilities in data processing, model optimization, and intelligent decision-making, can play a significant role in various passive safety development stages, including crash simulation, vehicle body structure optimization, and occupant protection system design. This paper systematically reviews the technical pathways and application practices of AI technology in the field of automotive passive safety. It analyzes the core shortcomings of current technology in practical implementation by combining authoritative data and typical enterprise case studies. Furthermore, considering industry policy directions, technological iteration trends, and market demand shifts, the paper prospects future development directions such as multimodal fusion, digital twin collaboration, and empowerment by domain-wide large AI models. The research aims to provide comprehensive technical references for relevant personnel, promote the deep integration of AI technology with automotive passive safety development, and contribute to the industry's goal of achieving a "zero-accident" safety target.