Leaders, practitioners and scientists' awareness of artificial intelligence in libraries: a pilot study

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Abstract

Purpose: This study investigates the level of artificial intelligence (AI) awareness among library leaders, practitioners and scientists of Indonesian academic libraries to elucidate the benefits of AI implementation and its necessary infrastructure and challenges. Design/methodology/approach: The study adopted a purposive sampling technique to select the 38 participants and thematic analysis to analyze the data, identifying eight themes: understanding of AI, AI adoption, benefits of AI, competencies needed to support AI, facilities to support AI, factors supporting AI adoption, AI-inhibiting factors and expectations of AI. Findings: Different viewpoints provided full awareness among library stakeholders and sufficient information to begin AI initiatives in Indonesian libraries as leaders, practitioners and scientists had a favorable, open and encouraging outlook on AI. Research limitations/implications: The study does not investigate variations in perspectives between the participants, but it examines their understanding of AI and elaborates the results into the concept of an intelligent library. Moreover, this study only uses samples from academic libraries. Practical implications: Libraries can take these results into consideration before implementing AI, especially in technology and facilities, librarian competency with regard to AI and leadership roles in AI projects. Social implications: Library boards and library associations can use this research as a source to create guidelines about AI implementation in academic libraries. Originality/value: The study addresses the gap in the research on university libraries' readiness and awareness to implement AI, especially in developing countries.

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APA

Harisanty, D., Anna, N. E. V., Putri, T. E., Firdaus, A. A., & Noor Azizi, N. A. (2024). Leaders, practitioners and scientists’ awareness of artificial intelligence in libraries: a pilot study. Library Hi Tech, 42(3), 809–825. https://doi.org/10.1108/LHT-10-2021-0356

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