Transport is a major contributor to greenhouse gas emissions in South Asia, where rapid urbanisation, rising vehicle use, and inadequate infrastructure create significant sustainability challenges. With the integration of artificial intelligence (AI) and intelligent mobility—including innovative traffic management, ride-sharing platforms, autonomous systems, and electric mobility—there is potential to transform emissions reduction and efficiency, as well as mobility operations. However, a lack of contextual, qualitative evidence—particularly in South Asia—limits understanding of the drivers, barriers, and enablers. This chapter addresses this gap by examining how AI and smart mobility solutions can help decarbonise transport in Sri Lanka, India, the Maldives, and Bangladesh. Data were gathered through 16 in-depth interviews with policymakers, transport authorities, technology providers, and mobility users. Thematic analysis identified four main themes: (1) optimisation of traffic flow and mobility systems through AI, (2) potential to adopt low-carbon transport alternatives, (3) ongoing barriers such as infrastructure gaps, affordability issues, and data governance, and (4) enablers: supportive policies and cross-country collaboration. Results suggest that, despite the promising potential of AI-enabled smart mobility to decarbonise transport, its adoption remains limited due to financial, institutional, and regulatory challenges. The chapter concludes by discussing practical, theoretical, and policy implications, emphasising inclusive and sub-region-specific strategies to promote sustainable and climate-resilient transport futures in South Asia.