Abstract
PurposePeople have utilized artificial intelligence (AI) reading assistants for study. This tool assists readers in summarizing the content of a book. However, the crucial factor in summarizing book content lies in the quality of the content by generative AI, as this quality affects readers’ willingness to use AI tools as reading aids. This study expands the acceptance architecture for artificially intelligent device use (AIDUA), integrates the concept of generative AI quality and proposes a new model for users’ continuous use of generative AI reading assistants.Design/methodology/approachThis study employed a quantitative approach. A total of 362 respondents were from Taiwan. This study used partial least squares structural equation modeling (PLS-SEM) to validate, aiming to identify factors influencing users’ continued adoption of AI reading assistants.FindingsThe results show that the quality of AI-generated content and readability significantly influence users’ performance expectations and effort expectancy. However, credibility and representationalness have different effects, impacting effort expectancy but not performance expectancy. These findings underscore the critical role of generative AI quality in shaping user expectations and their continued use of AI reading assistants.Originality/valueThis research is of great significance in examining the quality of generative AI. It establishes a theoretical framework applicable to future research, enabling industry players to understand better the pivotal role of generative AI quality in the operation of information services. And focus on using AI reading assistants, describing the specific use of AI for specific tasks.
Published Version
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