AI TOOLS IN DIGITAL TRANSLATION EDUCATION: A CASE FOR CURRICULUM INTEGRATION

Abstrak

The rapid integration of artificial intelligence into professional translation workflows has created a significant mismatch between what translation programs teach and what the industry now demands. This article argues, through a review of pedagogical literature, industry data, and curriculum analysis, that AI-assisted tools — including computer-assisted translation (CAT) software, neural machine translation (NMT) engines, post-editing workflows, and terminology management systems — must be treated as core competencies within digital translation courses, not as optional technical supplements. The evidence consistently shows that students trained with these tools develop sharper critical and linguistic judgment, enter the profession more confidently, and meet employer expectations more readily. The article concludes with concrete recommendations for curriculum designers and instructors.