APPLICATION STRATEGY ANALYSIS AND PRACTICAL SUGGESTIONS OF GENERATIVE AI IN SERVICE DESIGN
DS 136: Proceedings of the Asia Design and Innovation Conference (ADIC) 2024
Year: 2024
Editor: Yong Se Kim; Yutaka Nomaguchi; Chun-Hsien Chen; Xiangyang Xin; Linna Hu; Meng Wang
Author: Zhong, Shuxiao
Series: Other endorsed
Institution: Tongji University
Page(s): 458-466
Abstract
This study explores generative artificial intelligence (AI) application strategies in different stages of service design, focusing on how it can assist designers in improving efficiency and innovation capabilities in the process from service context, demand insight, and design generation to design execution. Through a systematic literature review and case analysis, this study reveals the advantages and limitations of AI in data analysis, creative generation, user interaction simulation, etc., especially in reducing human bias and improving the scientificity and accuracy of problem definition in the demand insight stage. This paper further proposes specific application suggestions for service design practice, aiming to help designers effectively integrate AI tools while maintaining the dominant position of human design, fully utilizing the automation capabilities of AI, and achieving breakthroughs in service innovation.
Keywords: Generative AI, service design, service demand insight, human-machine collaboration, design innovation, application strategy