The electric vehicle (EV) purchasing process is characterized by high cognitive complexity, uncertainty, and perceived risk due to unfamiliar technologies, infrastructure dependence, and rapidly evolving standards. As a result, manufacturers increasingly deploy artificial intelligence (AI)–powered chatbots to support consumers during the decision-making journey. This study examines the role of AI chatbots in accelerating consumer decision-making speed in the EV buying context, using Tesla’s direct-to-consumer digital sales model as an illustrative case. Drawing on interdisciplinary literature from consumer behavior, marketing, and technology acceptance, the paper identifies three key mechanisms through which chatbots influence decision efficiency: information compression, trust reinforcement, and personalized guidance. The analysis suggests that AI chatbots reduce cognitive load, enhance perceived transparency, and shorten evaluation cycles in high-involvement purchase decisions. By synthesizing existing empirical evidence and contextualizing it within Tesla’s digital ecosystem, this study contributes to emerging research on conversational AI in complex markets and offers practical insights for firms seeking to optimize AI-enabled sales strategies in the expanding EV sector.