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The Impact of Artificial Intelligence Technology on the Development of Translation in China



Author(s)

LIU Zhuo

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DOI:10.17265/2159-5836/2025.11.003

School of Foreign Languages, Harbin University of Commerce, Harbin 150028, China

This study investigates how artificial intelligence (AI) reshapes China’s translation industry through technological innovation, industrial restructuring, and talent demand evolution between 2015 and 2025. Analyzing empirical data from 500 translation enterprises (including 320 small and medium-sized enterprises [SMEs] and 180 large-scale corporations), 20 universities offering translation programs, and 12 key policy documents from China’s Ministry of Education (MOE), Cyberspace Administration of China (CAC), and Translators Association of China (TAC), we identify three distinct evolutionary phases of AI translation in China: rule-based systems (2010-2017), neural machine translation (NMT, 2018-2022), and large language model (LLM)-driven intelligent adaptation (2023-2025). Key findings reveal that AI boosts translation efficiency by 40-60% through human-machine collaboration—reducing technical document processing time from 72 hours to 18 hours for complex BRI infrastructure blueprints—and expands service coverage to 34 languages (including 12 non-common languages critical for BRI, such as Kazakh, Swahili, and Urdu). However, AI also exacerbates talent mismatch: by 2025, China faced a shortage of over 50,000 “AI-translation compound professionals” (individuals proficient in both translation and AI tool operation, corpus management, or LLM fine-tuning), particularly in high-stakes fields like legal contract translation and medical document localization. Ethical risks further challenge sustainability: a cross-sectional survey of 500 enterprises conducted in 2024-2025 found that 45% of SMEs violated data privacy regulations (e.g., using client confidential documents to train LLMs without consent), and 30% of LLM-generated literary translations infringed copyrights. Policy recommendations include aligning with China’s New Generation AI Development Plan (2024-2030) to accelerate domain-specific standardization (e.g., mandatory certification for legal and medical AI translation tools) and integrating AI literacy into translation curricula (e.g., mandatory “LLM Operation and Quality Assessment” courses in all undergraduate translation programs by 2026).

Artificial Intelligence, neural machine translation, large language models, human-machine collaboration, translation industry, China, belt and road initiative

Journal of Literature and Art Studies, November 2025, Vol. 15, No. 11, 820-828