Study on the Development Pathways of Translators’ Technological Competence in the AI Era

As AI technologies become deeply embedded in translation practice, the traditionally human-centered translation process is increasingly transforming into a multi-stage human–AI collaborative workflow, in which translation tasks are reconfigured into a series of sub-processes, including data preparation, prompt design, AI-assisted generation, and post-editing and quality control. Against this backdrop, this paper argues for the necessity of systematically enhancing translators’ AI literacy in order to cultivate their ability to effectively understand, manage, and apply AI-based translation tools in professional practice, while also emphasizing the functional positioning and operational mechanisms of AI across the entire translation workflow. At the same time, due attention must be paid to the potential risks posed by generative AI, particularly hallucination-induced errors, so as to ensure translation quality.