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A Study on the AI Adoption of Integrated Library Systems: Focusing on a Cross-Analysis of KOLAS Patch History and Domestic and International Solution and Research Trends

  • Journal of the Korean Society for Library and Information Science
  • 2026, 60(3), pp.165~188
  • DOI : 10.4275/KSLIS.2026.60.3.165
  • Publisher : 한국문헌정보학회
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : July 21, 2026
  • Accepted : August 10, 2026
  • Published : August 31, 2026

Gyeungsoo Kim 1 SION CHOI 2 Kim Seonghun 2

1성균관대학교 경영대학 핀테크융합전공
2건국대학교

Excellent Accredited

ABSTRACT

The aim of this study is to empirically identify areas where artificial intelligence (AI) can be applied to library automation systems used in day-to-day library operations. To investigate the requirements of library practitioners, 126 patches from KOLAS (2015-2026) were broken down into individual improvement items (653 in total); eight operational categories and five types of improvement were identified and subjected to a comprehensive analysis. Furthermore, a triangulation analysis was conducted by examining the publicly available AI features of domestic and international solutions alongside prior research. The results revealed that on-site improvement demands were concentrated on borrowing, returns and reservations (19.1%) and interlibrary loans (18.5%), whilst bug fixes accounted for 45.5%, confirming chronic vulnerabilities in data consistency and quality. Conversely, commercial AI has reached a mature stage in search, organisation and interlibrary loans, highlighting a gap between supply and demand. Based on this, cataloguing, search and acquisition were proposed as priority areas for implementation, whilst data quality improvement, strengthening of collection development, librarian review and policy monitoring were identified as factors to be considered when introducing AI functions. This study provides a basis for establishing functional requirements for libraries transitioning their systems ahead of the termination of KOLAS technical support, as well as for determining the direction of AI development in domestic solutions.

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