Artificial intelligence in academic libraries: LIS students’ perceptions, expectations and predictors

As academic libraries face increasing demands to provide efficient, personalized services in a rapidly evolving digital landscape, integrating artificial intelligence (AI) technologies offers transformative potential. This study aims to investigate LIS students’ expectations on the implementation of AI in academic library services in Bangladesh. The study used a quantitative approach to collect data from the respondents. 250 LIS students from three public and one private LIS degree-offering universities in Bangladesh participated in this study. Convenience sampling method was used to collect quantitative data from the students using an online survey questionnaire prepared using Google Forms. The findings reveal that LIS students hold positive perceptions of AI in academic libraries, identifying chatbots, voice assistants, and recommendation systems as key applications, particularly in information and reference services. Significant differences in expectations were observed across gender, education level and AI training, while internet proficiency strongly influenced optimism. Correlation results indicate that familiarity and frequency of AI use are positively associated with optimism and expectations. Regression analysis further shows that optimism, internet proficiency, gender, and education level significantly predict expectations. Overall, students demonstrate strong readiness for AI implementation, though perceptions vary based on experience and digital competence. While previous studies in Bangladesh have primarily explored AI implementation from the perspectives of library professionals, this study extends the literature by investigating LIS students’ perceptions, expectations, and their predictors regarding AI implementation in academic library services.