This review critically examines the transformative impact of Artificial Intelligence-Generated Content (AIGC) on each stage of product design, offering an integrative analysis of how generative tools reshape workflows, creativity, and evaluation criteria. This paper provides a comprehensive review of the applications, innovations, and challenges of AIGC in product design workflows, focusing on its roles in key stages such as requirement analysis, conceptual design, detailed design, and prototyping. The study highlights AIGC's notable advantages in sparking creativity, optimizing design tools, and fostering interdisciplinary collaboration. This study also identifies key limitations in current research, including an over-reliance on AI systems, the lack of empirical validation for proposed design frameworks, and insufficient exploration of human–AI co-creation mechanisms. The paper summarizes the core innovations of AIGC, including leveraging generative AI technologies to build customized databases and design models, integrating AIGC tools into modular design processes, and exploring innovative design frameworks. The authors also propose future research directions, such as optimizing human-AI collaboration models and expanding AIGC applications across various industries. Through this article, researchers, designers, and industry practitioners can gain valuable theoretical and practical insights to further leverage AIGC for driving continuous innovation in the field of product design.
Shi et al. (Thu,) studied this question.
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