In the modern era of diverse design tools, designers not only use computer-aided design (CAD) for product development but also incorporate generative artificial intelligence (AI) in recent times to assist in idea generation and iteration. Therefore, this study aims to develop a design method that integrates generative AI—primarily using ChatGPT—with the morphological chart method to create an AI-assisted design approach. Through practical case demonstrations, the study illustrates the application process of this method and gathers feedback from approximately five professional designers and other stakeholders (informed consent forms will be provided beforehand). The goal is to evaluate the rationality and practicality of the method and examine the pros and cons of empowering generative AI as a participant in design teams. The morphological chart [1] is a long-established divergent technique, commonly used in product design as a tool for expanding ideas. However, traditional methods like brainstorming or mind mapping, while effective in stimulating creativity, are often constrained by the designers’ personal experiences or cultural backgrounds, potentially missing out on more innovative solutions. This study employs the morphological chart by defining the parameters of individual components in the first column and using focus group discussions or brainstorming sessions within the design team to generate various possibilities in subsequent columns. Ultimately, the design team selects one option from each category for the final decision. In this research, ChatGPT is employed to generate possibilities for components by inputting instructions to produce related visual proposals (based on product definitions and the conditions set in the first column). These generated visuals serve as design suggestions, thereby improving efficiency and mitigating the influence of the design team's backgrounds and experiences on idea generation. After creating the morphological chart with the assistance of generative AI, the design team will exclude components with potential patent or plagiarism risks during the analysis phase. They will then select ten feasible options for final decision-making, which will lead to the production of a product—a dumbbell storage rack. The study collects approximately ten valid questionnaires through a survey (with informed consent forms provided in advance) and uses fuzzy comprehensive evaluation [2] to analyze and consolidate the results. The findings aim to confirm that the products developed using generative AI integrated with the morphological chart method meet public expectations and avoid infringement issues. In summary, this study will be conducted in three stages of analysis and discussion: