This study introduces and validates the artificial intelligence anxiety scale (AIAS), a novel instrument designed to measure researchers’ anxieties when employing artificial intelligence (AI) tools in academic writing. As AI technologies rapidly infiltrate scholarly work, however, the primary concern grows about their ethical implications, impact on traditional research skills, and the lack of institutional readiness issues that remain underexplored in existing literature. Addressing this critical gap, the AIAS offers a novel framework grounded in real-world academic concerns. Using an inductive approach, data were collected from 219 faculty members and graduate students at Taif University, Saudi Arabia, revealing four core dimensions of AI-related anxiety: (1) concerns about the accuracy of AI outputs, (2) fear of committing plagiarism, (3) lack of institutional guidelines, and (4) fear of losing research skills. Exploratory and confirmatory factor analyses confirmed the existence of these factors, and reliability testing indicated robust internal consistency. By offering the first validated tool specifically tailored to measure AI-related anxiety in academic contexts, this study provides a significant resource for researchers and institutions. Its application can guide universities in devising training and support initiatives to ensure the ethical and practical integration of AI, thereby sustaining the integrity of traditional research competencies and enhancing the overall quality and credibility of academic endeavors.
Alshaibani et al. (Mon,) studied this question.
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