The rapid proliferation of generative AI tools has reshaped brainstorming practices while introducing new technostress risks. Although prior studies have explored AI-induced technostress and its impact on user attitudes, the mechanisms through which specific AI characteristics trigger technostress in collaborative brainstorming remain unknown. To address this gap, this study applies the person–technology fit model to examine how key AI technology characteristics affect outcomes across two stages of brainstorming through technostress: creative performance during idea generation and idea selection preference during idea selection.
An online survey was conducted with 409 participants recruited via Credamo, a professional online survey platform in China. The collected data were analyzed using partial least squares structural equation modeling (PLS-SEM).
The results show that AI intransparency and knowledge hallucination positively influence AI control anxiety, which in turn negatively affects both user creative performance and user idea selection preference for AI-generated ideas. Furthermore, AI control anxiety mediates the relationships between AI technology characteristics and both creative performance and idea selection preference. Additionally, user coping flexibility was found to negatively moderate the relationship between AI control anxiety and creative performance, such that individuals with higher coping flexibility experienced a weaker negative effect of AI control anxiety on their creative performance.
This study revealed the antecedents of technostress in human–AI collaborative brainstorming from the perspective of AI technology characteristics. By introducing AI control anxiety as a key construct, this study extends the applicability of the person-technology fit model, and provides a new lens for understanding existing constraints in human–AI collaborative brainstorming tasks.
