Unveiling the Complexity of Designers’ Intention to Use Generative AI in Corporate Product Design: A Grounded Theory and fsQCA

While generative artificial intelligence (Gen AI) is accelerating digital transformation and innovation in corporate product design (CPD), limited research has explored how designers adopt this technology. This study aims to identify the key factors and causal configurations that influence designers’ intentions to adopt Gen AI in CPD. This study involved 327 in-service designers as participants, employed semi-structured interviews and a questionnaire to collect data, and applied the grounded theory and fsQCA to analyze the data. The findings indicate the following: (1) Personal innovativeness, AI technological anxiety, perceived usefulness, task–technology fit, perceived risk, social influence, and organizational support are the key factors influencing designers’ adoption of Gen AI. (2) None of these factors constitute a necessary condition for designers to adopt Gen AI. (3) High adoption intention results from the interaction of multiple factors, which can be categorized into three driving logics: “task demand-driven”, “organizational environment-driven”, and “individual characteristics-driven”. It is recommended that corporate managers establish an AI training framework, foster a supportive organizational environment, and implement tailored strategies to facilitate the integration of new technologies. This study clarifies the factors influencing designers’ adoption of Gen AI in CPD and provides a framework for companies to effectively integrate AI systems into product design.

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Publication Details

Journal
Systems
Published
2025-04-09
DOI
https://doi.org/10.3390/systems13040275
Citations
11
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
25.12
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article

Unveiling the Complexity of Designers’ Intention to Use Generative AI in Corporate Product Design: A Grounded Theory and fsQCA

Mingxi Shi, Qihan Guo, S. B. Kim, Peng Zhang et al.
11 citations
Systems
Big Data and Business Intelligence
25.12
article

Unveiling the Complexity of Designers’ Intention to Use Generative AI in Corporate Product Design: A Grounded Theory and fsQCA

Mingxi Shi, Qihan Guo, S. B. Kim, Peng Zhang, Li He, Yuqing Liu
article en
11 citations

Abstract

While generative artificial intelligence (Gen AI) is accelerating digital transformation and innovation in corporate product design (CPD), limited research has explored how designers adopt this technology. This study aims to identify the key factors and causal configurations that influence designers’ intentions to adopt Gen AI in CPD. This study involved 327 in-service designers as participants, employed semi-structured interviews and a questionnaire to collect data, and applied the grounded theory and fsQCA to analyze the data. The findings indicate the following: (1) Personal innovativeness, AI technological anxiety, perceived usefulness, task–technology fit, perceived risk, social influence, and organizational support are the key factors influencing designers’ adoption of Gen AI. (2) None of these factors constitute a necessary condition for designers to adopt Gen AI. (3) High adoption intention results from the interaction of multiple factors, which can be categorized into three driving logics: “task demand-driven”, “organizational environment-driven”, and “individual characteristics-driven”. It is recommended that corporate managers establish an AI training framework, foster a supportive organizational environment, and implement tailored strategies to facilitate the integration of new technologies. This study clarifies the factors influencing designers’ adoption of Gen AI in CPD and provides a framework for companies to effectively integrate AI systems into product design.

SystemsVol. 13(4)
Wuhan University of Technology (CN), Kyungpook National University (KR)
Openalex Percentile: Top 0%
Big Data and Business Intelligence
25.12
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Unveiling the Complexity of Designers’ Intention to Use Generative AI in Corporate Product Design: A Grounded Theory and fsQCA — Mingxi Shi, Qihan Guo, et al. · Systems (2025) | TGRS Research Map | TGRS