2026, Vol.27, No.3

The Journal of Translation Studies 2025 KCI Impact Factor : 2.77

pISSN : 1229-795X
https://journal.kci.go.kr/kats

The accelerating development of large language models and neural machine translation is reshaping the translation industry and challenging the sustainability of professional translators. As machine-generated output increasingly meets market demand for “good enough” translation, translators risk deprofessionalization, often relegated to repetitive post-editing. This study proposes a three-dimensional framework to strengthen professional resilience: posture transformation, redefinition of language proficiency, and identity reconstruction. First, translators must adopt a proactive “cyborg” posture, strategically integrating AI tools to achieve augmented translation that balances machine efficiency with human cognitive oversight. Second, language proficiency should evolve beyond replicable Basic Language Cognition toward Higher Language Cognition and specialized phraseological expertise. This positions translators as “Translation Connoisseurs” who critically refine AI outputs for nuanced cultural and contextual accuracy. Third, identity reconstruction is essential: translators should transition from “language converters” into “Translator Plus,” embracing roles as multilingual communication consultants and cultural mediators. Through digital branding, storytelling, and collaborative negotiation, they can secure sustainable, high-value positions in the AI-driven market. Ultimately, the future of translation lies in “integrated language mediators” who strategically employ AI while maintaining exclusive authority over advanced cognitive and cultural tasks, ensuring long-term professional sustainability.

This study addresses the significant gap between the rapid transformation of the language industry driven by artificial intelligence (AI) and the adaptation of translation and interpreting education to this changing environment. Drawing on recent industry reports from CSA Research, Nimdzi Insights, and Slator, together with Intento’s report on the state of translation automation, the study examines changes in the global language industry across four dimensions: market size and industry structure, business models and service types, technology, and talent. Based on this analysis, the study identifies the core competencies required of translation and interpreting professionals in an evolving industry environment. It then maps these competencies onto specific curricular content and pedagogical approaches and proposes new educational objectives and directions for innovation in translation and interpreting education in the AI era.

Although the current system has established a basic institutional foundation for training and assessing medical interpreting personnel, its legal status and post-examination management framework remain insufficiently developed. This article examines the regulatory frameworks governing International Medical Tour Coordinators and medical interpretation service personnel and compares them with those applicable to analogous interpreting professions. It identifies three structural problems: the absence of qualification status for medical interpreting personnel, the lack of a post-examination management framework, and the limited capacity of the term “Medical Interpreting Proficiency Test” to reflect the professional nature of medical interpreting. To address these issues, this study proposes a phased approach to institutional reform. In the short term, the current “Medical Interpreting Proficiency Test” should be renamed as a “certification assessment” or “certification examination”. Continuing education should also be made mandatory through amendments to the relevant Act and subordinate regulations, while the integrated public notice should establish detailed standards governing its frequency, methods, content, completion requirements, and record management. In the long term, the system should be developed into a national qualification or an equivalent public certification system.