In the field of vehicle design, the vehicle rear lamp is an indispensable part of the vehicle body. The function of the lamps is not only warning lighting. All car manufacturers are committed to integrating corporate brand characteristics and the most advanced technology with the vehicle lights for series design. In contemporary vehicle design, car lights have gradually become an important window for major car manufacturers to display their technical capabilities and aesthetic creativity. Among them, the design of lamps for commercial vehicles is the most difficult. Since commercial vehicle lamps have more stringent requirements for safety, visibility, and durability, in the process of designing traditional commercial vehicle taillights, especially in the R&D and design stage of car lights, a lot of manpower and time are spent. With the vigorous development of generative artificial intelligence (Generative AI, GenAI) technology, it brings the possibility of innovation to the design field. For industrial designers, applying GenAI's image generation function can quickly transform abstract concepts into conceptual images that meet their own expectations and have exquisite images, effectively improving design efficiency and innovation. Therefore, this study explores the application of the drawing design function of generative artificial intelligence in the design of commercial vehicle taillights like how to effectively integrate GenAI technology in the design process of commercial vehicle taillights and establish an optimal design process for such design needs. This research is conducted in four phases. In the first phase, “AI expert consultation”, the research team invites experts with rich practical and teaching experience in GenAI to conduct in-depth interviews. The experts are asked to share their insights and recommend the most suitable GenAI software to assist in joint review and correction. The preliminary structure of GenAI introduced into the new product development and design process proposed at the beginning of this research. The second phase of “Expert Consultation for Car Lighting Enterprises” invites car lighting design experts from Taiwan's largest commercial vehicle rear lamp design company to consult on the company's car lighting design process, find the right time to introduce GenAI, and collaborate with designers in charge of each design stage to try out GenAI software. The third phase, “GenAI design process revision”, aims to broaden the application scope of GenAI in the design process. To achieve this, cross-disciplinary designers are invited to conduct process tests. The test results are then provided to automotive lighting design experts for review, helping to refine and establish the design process proposed by the research team. In the fourth stage of “GenAI design process verification”, thirty entry-level designers are sought to test the GenAI car light design process to verify the feasibility and effectiveness of the method and process. This study compiled the global iconic brands and products of commercial vehicle rear lamps, the GenAI abstract drawing generation formula for rear lamps, the GenAI concrete drawing generation formula for rear lamps, and the most appropriate time to introduce GenAI generative artificial intelligence into the commercial vehicle rear lamp design process. Considering that GenAI must have certain feasibility in the actual manufacturing process, and based on the above-mentioned output results for technical integration, this study finally proposes the “Optimum Introduction of GenAI into the Rear Lamp Design Process of Commercial Vehicles”, which can be used by various companies in the future to study GenAI-related applications and refer to it when introducing their own design process, and hope that the results of this research can bring innovative design possibilities to the industry and bring more innovation opportunities to industrial designers.