AI-Powered Translation and the Reframing of Cultural Concepts in Language Education

This study examines how artificial-intelligence (AI) technologies reshape cultural concepts in the domains of translation and language education. By analyzing the ways AI facilitates precise cross-lingual transfer while adapting cultural elements during translation, we show how intelligent machine-translation (MT) systems guide users toward deeper understanding of target-language cultures and ultimately influence their own cultural identities. The paper also investigates AI-powered online language-learning platforms, exploring how they embed cultural content into course design and pedagogy to enhance learners’ intercultural communicative competence. Case studies reveal that AI not only boosts linguistic accuracy but also opens new educational models and practical pathways for cultural integration—such as personalized learning schemes grounded in big-data analytics and natural-language processing (NLP). Consequently, the wide deployment of AI supplies technological support for culturally responsive language education, promotes more profound and effective intercultural exchange, and fosters cultural understanding and identification in today’s globalized context. The findings provide theoretical underpinnings and practical directions for future translation and language-education practice, while opening new perspectives for interdisciplinary research between AI and the humanities.