Innovating Quality Management Mindset: A Foundation for Smart and Sustainable Road Transportation

ABSTRACT The effective management of road infrastructure is critical to achieving sustainable development goals, particularly in developing countries. This study investigates the integration of Artificial Intelligence (AI) into road maintenance management by employing two complementary approaches: (i) technical experimentation through the application of the YOLOv6 model for automated road damage detection, and (ii) an institutional readiness assessment conducted via a structured survey involving 50 technical staff members from Jamaica's National Works Agency (NWA). The YOLOv6 model was trained on more than 15,000 annotated images and subsequently deployed on selected urban roads in Jamaica. This implementation led to an improvement in detection accuracy ranging from 15% to 29% compared to traditional manual inspection methods. In parallel, the survey results indicated a high level of awareness regarding AI's potential; however, significant challenges were identified, including implementation costs, insufficient technical expertise, and data quality limitations. These findings underscore that digital transformation in road infrastructure management extends beyond technical considerations. It constitutes a multifaceted process requiring coordinated efforts across technological, organizational, and regulatory dimensions. Therefore, the integration of AI into Jamaica's road infrastructure strategy must be aligned with national development priorities, underpinned by strategic policy frameworks and sustained investment. This study not only demonstrates the technical and institutional feasibility of AI‐driven road management systems but also provides policy‐relevant insights for promoting scalable and context‐sensitive digital transformation within the transportation sector of developing countries.