Impact of AI on Legal and Institutional Translation: Issues and Strategies

Abstract

The rapid development of Artificial Intelligence (AI) has drastically transformed the sphere of legal and institutional translation. This article critically examines the various impacts of AI-based translation technologies, that is, Neural Machine Translation (NMT) and Large Language Models (LLMs), on the accuracy, reliability, and ethical implications of legal and institutional translation. Drawing on a comprehensive literature review, theoretical models of translation studies and technology acceptance, and case analysis of the European Union, United Nations, and multinational law firms, the article identifies the key issues such as ambiguous terminology, jurisdiction, data privacy, and loss of employment. As the analysis shows, the existing AI systems face the problem of system-based legal terminology, cultural and legal context, and risks of bias and accountability failures. The article subsequently recommends several measures to be taken, including people-involving workflow, training AI customization, robust quality assurance processes, and professional growth of translators. New trends, including the emergence of real-time legal translation, law reform, and the increasingly important role of translators as AI supervisors and moral gatekeepers are also discussed. The article concludes by emphasizing that responsible, ethical, and co-working innovation is instrumental in ensuring that AI becomes a capable partner in the battle to ensure justice, clarity, and understanding of the law in the multilingual legal practice.