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The Use of Generative AI Technologies in Electronic Records Management and Archival Information Service

  • Journal of Korean Society of Archives and Records Management
  • Abbr : JRMASK
  • 2023, 23(4), pp.179~200
  • DOI : 10.14404/JKSARM.2023.23.4.179
  • Publisher : Korean Society of Archives and Records Management
  • Research Area : Interdisciplinary Studies > Library and Information Science > Archival Studies / Conservation
  • Received : October 17, 2023
  • Accepted : November 21, 2023
  • Published : November 30, 2023

Yoona Kang 1 Hyo-Jung Oh 2

1전북대학교 일반대학원 기록관리학과 박사과정
2전북대학교 기록관리학과 교수,문화융복합아카이빙연구소 공동연구원

Accredited

ABSTRACT

Records management institutions in Korea generally face a situation where they lack the workforce to manage the vast amount of electronic records. If electronic records management tasks and archival information services can be automated and intelligentized, the workload can be reduced and the service satisfaction of users can be improved. Therefore, this study proposes to utilize “generative AI” technology in records management practice. To achieve this, the study first examined previous research that aimed to intelligently automate various tasks in the field of records management. The fundamental concepts of generative AI were subsequently outlined, and domestic cases of generative AI applications were investigated. Next, the scope of applying generative AI to the field of records management was defined, and specific utilization strategies were proposed based on this. Regarding the strategies, the effectiveness was verified by presenting results from applying commercial generative AI services or citing examples from other fields. Lastly, the benefits and implications of using generative AI technology in the field of records management, as well as limitations that must be addressed in advance, were presented. This study holds significance in that it identified tasks within the field of records management where generative AI technology can be integrated and proposed effective utilization strategies tailored to those tasks.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.