The fuel consumption optimization using artificial intelligence-powered driver behavior analysis a way forward for greener roads analyzing driver behavior critically in road transport becomes essential to increasing fuel efficiency and attaining environmental sustainability. This study explores how artificial intelligence (AI) can be used to analyze and improve driver behavior in order to maximize fuel efficiency. The study shows how dynamic monitoring of driving habits and real-time feedback can result in significant fuel usage savings by utilizing AI's sophisticated learning capabilities. Artificial intelligence (AI) systems can detect inefficiencies and recommend behavioral changes to drivers by analyzing complicated data, including acceleration, braking patterns, and idle times, using advanced machine learning models. The paper examines the various obstacles that come with using AI for this purpose, such as worries about data privacy, the reliability of AI in different traffic and weather scenarios, and the human element. At the same time, it demonstrates the wide range of possibilities AI offers, including improved predictive accuracy and the potential for customized driver training programs. The study highlights the role of AI in paving the way for greener roads by discussing these opportunities and obstacles. © 2025 Elsevier B.V., All rights reserved.