第108回アジア太平洋研究センター（WIAPS）研究会 (11/9)

開催日時

2026年11月9日（月）12:25-13:00

場所

ZOOMウェビナー

参加資格

WIAPS専任教員・助教, GSAPS兼担教員, WIAPS受入の交換研究員・訪問学者・外国人研究員, GSAPS修士課程・博士後期課程在学生

報告者

グエン アン ハオ（早稲田大学アジア太平洋研究センター助教）

報告テーマ

 From technostress to problem-solving: Examining the roles of AI overuse and AI competencies.

（使用言語：英語）

要旨

As artificial intelligence (AI) tools become increasingly integrated into academic and workplace settings, individuals face growing technological pressures alongside rising performance demands. At the same time, AI offers new opportunities to improve work performance, particularly in problem-solving. However, limited research has examined the mechanisms through which technostress influences problem-solving performance in the context of AI use. Drawing on stress and coping theory, this study investigates impact of techno-stressors (including five dimensions including techno-complexity, techno-insecurity, techno-invasion, techno-overload, and techno-uncertainty) on problem-solving through the AI overuse as a behavioral coping response and moderating effects of interpersonal influence, question formulation and judging results. Data samples of 673 individuals were collected in Vietnamese context from November 2025 to January 2026 via a non-probability convenience sampling technique through an online questionnaire survey. Data was analyzed using measurement test, structural equation modeling and multiple linear regression analysis. The findings reveal that techno-stressors have significant positive effects on both AI overuse and problem-solving. However, the moderating effect of interpersonal influence is not supported. AI overuse also has a positive effect on problem-solving, suggesting that frequent AI use can provide cognitive support and facilitate access to relevant information. Nevertheless, this positive relationship becomes weaker among individuals with stronger question formulation skills, possibly because excessive AI interaction provides limited additional value to those who can already formulate effective questions. Interestingly, this negative moderating effect is reversed when individuals also have strong abilities to evaluate AI-generated results. This three-way interaction suggests that combining effective question formulation with critical evaluation enables individuals to use AI more actively and effectively, while reducing the risks associated with inaccurate or misleading AI-generated information.

This study contributes to the technostress and human–AI interaction literature by showing that AI overuse does not necessarily lead to negative outcomes but can also serve as a useful source of cognitive support for problem-solving. It further highlights the importance of considering the combined effects of AI competencies including input and output evaluation skills when examining the relationship between AI use and performance. Practically, the findings suggest that organizations and educational institutions should move beyond basic prompt-writing training and implement more comprehensive practices to develop AI literacy. Such training should combine effective question formulation with critical evaluation and verification of AI-generated results to help individuals translate intensive AI use into enhanced performance.