Research on AI-Driven Business Translation for Enterprise Globalization

With the deepening of the “Belt and Road” Initiative, Chinese enterprises are accelerating their globalization process, leading to an exponential growth in demand for high-quality business translation. This paper constructs an AI-driven business translation system model tailored for enterprise globalization scenarios, based on Natural Language Processing (NLP) technology and the Neural Machine Translation (NMT) framework. Through questionnaires, in-depth interviews, and comparative experiments with 218 globalized enterprises, combined with SPSS quantitative analysis and Nvivo qualitative coding, the application effectiveness of AI translation in scenarios such as cross-border contracts, product localization, and cross-cultural marketing is systematically verified. The study finds that a hybrid translation model integrating domain knowledge graphs significantly improves the accuracy of professional terminology; dynamic context adaptation technology greatly enhances cultural adaptability; and the human-machine collaboration mode yields promising cost reductions compared to purely human translation. The research results provide theoretical support and practical pathways for the industrial application of intelligent translation technology.