This study focuses on the integration of artificial intelligence (AI) tools into the concept development and product development phases in industrial design processes and the effects of these AI tools on the final product (physical/digital prototype). The aim of this study is to provide an insight into how image generating AI tools can be integrated into the industrial design process and to comparatively examine the relationship between AI-physical product and AI-digital product in the design process. This study, which was piloted in the spring semester of 2023-2024, has been funded by the University for one year as of November 2024 within the scope of “scientific research project supported by higher education institutions”. Within the scope of this project, a design project was carried out with a total of 23 students enrolled in the Experimental Design elective course at the Department of Industrial Design, in the fall semester of 2024-2025. The brief was to create a universe and creatures inhabiting it to be developed further as designer toys. The task was to use generative AI for concept and product development. The prototyping phase included two parallel processes: physical prototyping (3D printing) and digital prototyping (augmented reality). The students created CAD models based on the final AI-generated versions of the designer toys for manufacturing and built physical models. Simultaneously, they revised the final AI-generated images and CAD models for an augmented reality platform (digital prototypes). At the end of the semester, five designer toy sets were exhibited and obtained national design registration.

In order to monitor the development of the designs during the semester, the student works (prompts, generated images, CAD models, etc.) was collected weekly on Miro. These works were evaluated by the researchers in terms of the functioning of the design process and interpreted together with other collected data. At the end of each phase of the design process (concept development, product development, prototyping), a reflection questionnaire was applied in order to understand the students' experiences with the use of AI and the effects of AI on the design process. In addition, a focus group was conducted with each student group after the completion of the course and they were asked to discuss their experiences at each phase. The data collected from the questionnaires and focus groups were analyzed using content analysis.

The findings indicate that AI-assisted ideation enhanced creativity and visual communication, accelerating 2D conceptualization with high-quality imagery. However, transitioning from AI-generated concepts to physical and digital prototypes posed challenges, particularly in adapting outputs to CAD modeling and manufacturability. Physical prototyping was time-consuming and costly, requiring significant effort, while digital prototyping was faster, cost-effective, and interactive. Yet, students emphasized that they did not perceive digital prototypes as finalized, completed versions of their designs due to the lack of physical interaction. Despite these challenges, both students and instructors found the process engaging and innovative, highlighting AI as a valuable tool in the design process and education. AI not only improved visualization but also reshaped how students approached feasibility, emphasizing the need for further research on AI integration in industrial design.

Keywords: Design education, artificial intelligence, industrial design.