Enhancing translator employability in the artificial intelligence era

This exploratory study investigates Enhancing Translator Employability in the Artificial Intelligence Era (AI). As AI, particularly through machine learning and neural networks, revolutionizes translation services, concerns have emerged regarding the future demand for human translators.The study sets out to assess perceptions of employability among trainee translators. Translators and employers in the Artificial Intelligence Era (AI) era, identify factors influencing these perceptions, and propose strategies for enhancing their employability. Employing a mixed-methods approach with 60 participants—comprising 40 ASTI trainees, 16 recent graduates, and 4 employers—the study examines perceptions of future career prospects, factors influencing these perceptions, and strategies for enhancing employability. The research draws on Skills-Mismatch Theory, Human Capital Theory, Career Adaptability Theory, and Job-Market Signaling Theory guiding our research and findings. Results highlight significant uncertainty among trainees, largely due to the rapid integration of AI tools in translation. However, the study also reveals opportunities for human translators to adopt AI as a complementary tool, emphasizing the importance of targeted training programs in technological proficiency and adaptive skills.The study provides actionable recommendations, including curriculum reforms to incorporate AI-focused training, industry-academia collaborations, and the promotion of lifelong learning to ensure translators remain competitive. These findings offer insights into the evolving translation market and guide educational institutions, policymakers, and industry stakeholders in preparing translators for an AI-enhanced professional landscape.