Purpose This study aims to explore how translation students perceive and engage with artificial intelligence (AI) technologies within translation education, focusing on their applications, preparedness, challenges and expectations for future training. Design/methodology/approach Guided by Constructivist Learning Theory, a qualitative research design was employed. Open-ended responses were collected from 45 translation students through an online survey. A thematic approach was used to analyze the data, focusing on their perceptions, readiness and limitations of AI use in translation education. Findings Three thematic dimensions were identified: (1) Perceptions of AI Integration. Students generally recognize the benefits of AI, including improved efficiency, productivity and translation accuracy, while expressing concerns about overreliance, potential job displacement, and the erosion of human creativity; (2) Student Readiness for AI-assisted Translation. Students’ exposure to formal AI training and their frequency of self-directed use vary widely, resulting in different levels of self-efficacy. (3) Challenges and Future Prospects. Students identified challenges such as AI’s lack of contextual and cultural interpretation, ethical concerns including plagiarism and data privacy, and technical limitations in quality control. Practical implications Theoretically, this study extends Constructivist Learning Theory, demonstrating that students’ self-efficacy and learning outcomes are significantly shaped through authentic engagement with AI tools, reflective practice and hands-on, technology-mediated translation activities. Pedagogically, the findings highlight the necessity for translation education to move beyond introductory exposure to AI and incorporate systematic instruction in areas such as prompt engineering, critical evaluation of AI-generated output and opportunities for collaboration with industry partners, thereby preparing students to become critical, ethical and competent users of AI in professional translation contexts. Originality/value This study contributes novel insights by foregrounding student voices in the discourse on AI integration in translation education, an area often dominated by instructor-focused or technical research. It provides actionable recommendations for curriculum reform to better prepare future translators in the era of AI.
Yang et al. (Mon,) studied this question.