Abstract
Purpose
This study examines how academic libraries can support AI literacy through technological play, informal learning, librarian mediation and technology-rich spaces. It argues that AI literacy is sociotechnical: access to tools is necessary but does not by itself produce meaningful participation. The study also considers how institutional resources, governance and professional authority shape who can develop, support and benefit from AI-related learning.
Design/methodology/approach
Using a qualitative critical interpretive design, the study analyzes library and information science scholarship, professional frameworks, and selected institutional and higher education documents published between 2010 and 2026. Critical discourse analysis identifies recurring narratives of innovation, access, experimentation and professional responsibility. A political-economy lens examines the material and organizational conditions including funding, staffing, infrastructure, professional development, workload and governance that enable or constrain participation.
Findings
Four interrelated patterns emerge. Academic libraries are framed as sites of technological promise and innovation; librarians mediate AI learning through instruction, consultation, ethical guidance and collaborative problem-solving; technology-rich environments can support exploratory and play-based engagement; and opportunities for participation are unevenly shaped by funding, staffing, infrastructure, professional development, governance and institutional authority. AI literacy therefore develops through the interaction of tools, spaces, labor, pedagogy, experimentation and institutional conditions rather than through access alone.
Research limitations/implications
As a conceptual, document-based study, this research does not measure AI learning or library practice across a representative sample of institutions. Its findings are interpretive and should be tested through multi-site case studies, observations, interviews and comparative research across institution types. A systematic or scoping review is also needed to map the empirical evidence on AI literacy, technological play, library space, librarian labor and institutional conditions.
Practical implications
Library leaders should complement AI-tool provision with sustained investment in staff expertise, protected professional-development time, accessible infrastructure, low-risk opportunities for experimentation, clear policy guidance and meaningful participation in campus AI governance. Makerspaces, learning commons, workshops, sandboxes, consultations and peer-learning opportunities can support critical engagement when they are paired with human guidance and institutional support.
Social implications
Equitable AI literacy requires more than nominal access to generative AI tools. Differences in institutional funding, staffing, expertise, time and decision-making authority can shape learners' opportunities to experiment, question AI outputs, receive support and develop informed judgment. Academic libraries can help reduce these inequities by creating inclusive conditions for critical participation, reflection, and informed non-use alongside skill development.
Originality/value
The study integrates AI literacy and Technological Play Theory with a sociotechnical and political-economy account of academic library space, librarian labor, institutional resources and governance. It distinguishes access from meaningful participation and frames academic libraries as environments where technological, human, spatial, and organizational capacities converge. This framework offers researchers and library leaders a more comprehensive way to evaluate AI-learning initiatives beyond counting usage of tools, licenses or workshops alone.