Asian Journal of Economics, Finance and Management

Artificial intelligence (AI) is increasingly reshaping transportation through predictive analytics, intelligent infrastructure, connected mobility, autonomous systems and energy-responsive transport management. This systematic evidence review examines the AI-smart mobility nexus with an emphasis on intelligent transportation infrastructure and operational sustainability. Following PRISMA 2020, 30 eligible sources published between 2015 and 2026 were synthesised from Scopus, Web of Science, IEEE Xplore, ScienceDirect and Google Scholar. The corpus comprised 29 review, survey, meta-review, bibliometric or conceptual syntheses and one case study; accordingly, evidence was interpreted qualitatively and no pooled effect estimates were calculated. Five dominant domains emerged: AI-enabled traffic management, connected transportation infrastructure, safety and risk reduction, electric and renewable-energy-integrated mobility, and operational sustainability. Across the included literature, AI was generally associated with improved prediction, routing, incident recognition, system coordination, infrastructure monitoring and energy-management capability, although transferability depended on data quality, connectivity, infrastructure readiness, grid capacity and institutional capability. Operational efficiency did not consistently imply broader environmental or social sustainability. Interpreted through Technological Innovation Systems and Sustainability Transition perspectives, the evidence suggests that sustainable smart mobility depends on coordinated technological, infrastructural, institutional and energy-system development. The review therefore supports a qualified conclusion: AI can contribute to safer and more efficient mobility, but stronger primary, longitudinal and geographically diverse evidence is needed to establish durable environmental and social outcomes.