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Artificial intelligence (AI) integration is fundamentally transforming information literacy and library-based research, often without student awareness or institutional review. As database vendors embed AI capabilities such as article summarization, enhanced search, and clinical decision support into familiar resources, students are increasingly engaging in a collaborative process that redistributes core tasks like source selection and information synthesis. This shift moves the research workflow from student-led inquiry toward machine-guided assistance. This article offers a conceptual analysis and theoretical framework for understanding this redistribution of agency, aiming to equip educators and librarians with vocabulary to address these changes and to pave the way for future empirical work. Without intervention, students risk becoming passive passengers in their own research process, potentially undermining the traditional goals of information literacy grounded in autonomy and deliberate practice. To ensure that AI enhances rather than replaces critical thinking, academic libraries must champion transparency, preserve choice in research methods, provide comprehensive AI literacy instruction, and maintain institutional accountability through ongoing assessment.
Quincy Dalton McCrary (Fri,) studied this question.