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A Methodological Study on the Use of Generative AI in Legal Organizations

  • Legal Theory & Practice Review
  • Abbr : LTPR
  • 2026, 14(1), pp.177~204
  • Publisher : The Korea Society for Legal Theory and Practice Inc.
  • Research Area : Social Science > Law
  • Received : February 7, 2026
  • Accepted : February 23, 2026
  • Published : February 28, 2026

Lee, Kyung-Min 1

1한려대학교

Accredited

ABSTRACT

Generative AI technology based on large language model(LLM) is rapidly spreading across the legal field.. AI is already being utilized as a practical assistance tool in diverse areas, including case law and statute research, legal document drafting, issue organization, and contract review. In some areas, it is even attempting higher-level functions such as judgment prediction and risk analysis. These changes are bringing about a substantial shift in the work methods of legal professionals (judges, prosecutors, and lawyers, etc.). However, legal professionals are not simply providers of specialized services; they are normative professions responsible for the public functions of establishing and maintaining the legal order, guaranteeing fundamental rights, and realizing justice. Therefore, the use of AI in legal professionals raises questions beyond the issue of technological efficiency; its compatibility with the methodological structure of legal judgments may be questioned.. Generative AI in legal professionals can generate plausible legal texts, but this does not guarantee the legitimacy of legal judgments. Legal judgment is not a matter of statistical probability or pattern recognition, but rather a matter of normative choices based on authoritative legal evidence and the presentation of responsible justifications for those choices. In this regard, assuming AI as a decision-maker or using it in a way that effectively binds the outcome of a decision is difficult to accept from a legal methodology perspective. This paper examines whether the use of AI in legal judgment is compatible with the methodology of legal judgment and proposes normatively acceptable scope and limits. To this end, this paper focuses on the methodological characteristics of legal judgment and legal judgment, the types of generative AI applications in legal judgment, key issues surrounding the use of generative AI, and an analysis of the latest guidelines for the use of generative AI in the United States and Europe.

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