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This study examines human–AI collaboration in immersive simulation–enhanced product design through an autoethnographic comparison of conventional and AI-assisted workflows. Using the conceptual design of an electric motorbike as a representative case, the author conducted two parallel design processes: one following a traditional human-centered approach and the other integrating AI-supported ideation through the Vizcom AI platform. In both workflows, SolidWorks was used for parametric modeling, and Unreal Engine served as an immersive simulation environment enabling high-fidelity visualization, interaction, and virtual evaluation under consistent conditions. The workflows were evaluated using a shared set of qualitative and semi-quantitative metrics, including design innovation, aesthetic coherence, functional usability, manufacturability, and cognitive load. Data were primarily derived from structured reflective journaling, documenting decision-making rationales, iteration cycles, and experiential differences between AI-assisted and non-AI processes. The comparative analysis reveals that AI support substantially accelerates early-stage ideation and increases formal diversity and visual novelty. However, AI-generated proposals frequently required human correction and contextual judgment to address usability and manufacturability constraints. The immersive simulation environment facilitated iterative assessment by enabling real-time evaluations of spatial, ergonomic, and interaction-based aspects across both workflows. Rather than positioning AI as a substitute for human expertise, the findings highlight a shift in the designer’s role toward curation, critical evaluation, and interpretive control. The study contributes a transparent, process-oriented framework for examining human–AI collaboration in product design, offering insights that are transferable to a broad range of smart and interactive product development contexts.
Hüseyin Özkal Özsoy (Sun,) studied this question.
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