Mapping AI Competencies in Library and Information Science Education: Evidence From Gen Z Students

Purpose: This study examines artificial intelligence (AI) literacy and its influence on the adoption of human-centered AI among Generation Z (those born between 1997 and 2012) in Pakistan pursuing education and career in Library and Information Science (LIS). Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) and UNESCO’s AI Competency Framework, the study examines how AI literacy and awareness of human agency shape students’ behavioral intention and actual use of AI in academic research. Methodology: A quantitative survey design was employed, with convenience sampling. Data were collected from 680 MPhil and PhD LIS research students enrolled in seven universities. Descriptive and inferential statistical techniques, including correlation analysis, multiple regression, and moderation analysis, were used to test the proposed research model. Findings: The results indicate that performance expectancy, effort expectancy, and AI literacy have significant positive effects on students’ behavioral intention and academic performance with AI. In this study, AI literacy was conceptualized as a competency-based antecedent and was found to be the most effective predictor of AI adoption; it was not examined as an outcome of prior adoption. Social influence showed mixed effects: it sometimes discouraged adoption when ethical or academic concerns were present, while facilitating conditions had a limited impact. Human agency awareness negatively influenced adoption, reflecting students’ concerns about academic integrity, autonomy, and over-reliance on AI. Behavioral intention was the strongest determinant of actual AI usage. Age and gender moderated selected relationships, whereas qualification level and university type did not. Implications: The findings demonstrate that AI adoption among Gen Z LIS students is primarily literacy-driven and human-centered rather than infrastructure-driven. Universities and academic libraries must prioritize AI literacy education, ethical guidance, and human-centered AI training within LIS curricula to support responsible, effective, and sustainable AI integration in higher education.