Current generative artificial intelligence is deeply intervening in translation practice, driving translation activities from a relatively closed process of bilingual transfer to a complex practice involving the collaborative participation of humans, models, corpora, tools, and contexts, and thereby reshaping the competence objectives, teaching processes, assessment criteria, and ethical boundaries of translation education. At present, translation education faces challenges such as the weakening of learners’ agency, increasing pressure on teachers to transform their roles, declining validity of final product evaluation, rising risks of academic integrity, and blurred boundaries of translator responsibility. Translation education should be restructured around competence objectives, curricular content, teaching models, assessment systems, and ethical norms, and should build a translation competence cultivation framework centered on human machine collaboration competence, translation diagnostic competence, process management, and responsible ethics, so as to develop a new generation of translation professionals equipped to adapt to the intelligent language service ecosystem.