Artificial Intelligence Self-Efficacy: A Study of Academic Librarians

Abstract

Artificial Intelligence (AI) is considered as one of the important change agents in academic libraries owing to their role in managing information, offering digital services, and boosting engagement of users. In this study, the objective is to examine the level of AI self-efficacy amongst academic librarians and influence of AI self-efficacy on AI adoption, professional competency, and digital transformation in academic libraries. The quantitative cross-sectional research approach has been used in which a questionnaire-based method has been followed for the purpose of data collection among 250 academic librarians from public and private universities. The statistical tests, including descriptive statistics, Pearson correlation, and multiple regressions, were performed on the data. The findings have shown that the total score of AI self-efficacy is 4.08/5.00 and the total score of AI adoption is 3.97/5.00. The correlation test has shown a strong positive relationship between AI self-efficacy and AI adoption (r=0.746, p<0.001), professional competency (r=0.711), service innovation (r=0.695), and digital transformation (r=0.758). The findings from regression analysis revealed that the self-efficacy of AI had considerable influence on digital transformation where the value of R² was estimated at 0.521, which implies that 52.1% of the changes in the use of AI can be accounted for by AI self-efficacy. Out of all the perceived benefits of the use of AI, the rapid access to the required information was reported by 85.6% of the respondents, whereas improvements in users’ services were reported by 80.4%. However, not having enough AI training (68.0%), no technological knowledge (64.8%), and insufficient financing (61.6%) emerged as the primary barriers to implementation.