Enhancing Translation Services in Jordan through Technology: A Study of Specialization Trends and Language Adaptations

This study investigates the influence of advanced technological integration, particularly artificial intelligence (AI) and neural machine translation (NMT), on the specialization trends and language adaptation strategies within Jordan's translation industry. Despite technology’s promising potential to enhance translation efficiency and expand market reach, concerns persist regarding AI's limited ability to accurately grasp contextual nuances, especially in linguistically and culturally diverse languages like Arabic and English. The study aims to identify current technological usage levels among translation service providers, examine how technology influences specialization within legal, medical and technical translation sectors, and explore language adaptation strategies employed to manage AI-driven translations. The Technology Acceptance Model (TAM), introduced by Davis (1989), serves as the theoretical framework to assess translators' perceived usefulness and ease of use of these technologies. A qualitative approach employing purposive sampling involved ten participants representing diverse roles in Jordan’s translation industry. The obtained findings indicate significant shifts from traditional manual translation to specialized roles emphasizing quality assurance, post-editing, and terminology management; reveal increased emphasis on cultural localization strategies; and highlight challenges such as AI’s limited cultural comprehension, extensive post-editing requirements and data privacy concerns. The study provides recommendations for educational and operational adjustments to enhance technological integration in translation practices.