Navigating AI-Driven Translation in Saudi Arabia's Media: Challenges and Opportunities
DOI:
https://doi.org/10.63939/AJTS.91zp6t15Keywords:
AI-Driven Translation, Cultural Adaptation, Media, Vision 2030Abstract
This study investigates the integration of Artificial Intelligence (AI) in Saudi Arabia’s media translation industry within the framework of Vision 2030. As AI increasingly supports global translation practices, Saudi Arabia faces a pressing challenge: how to adopt these tools without compromising linguistic precision and cultural fidelity, particularly in media content rich with idioms, religious references and traditional expressions. The study adopts a hybrid theoretical framework combining the Unified Theory of Acceptance and Use of Technology (UTAUT) by Venkatesh et al. (2003) and Cultural Adaptation Theory (CAT) by Kim (1988) to explore both technological usability and cultural sensitivity. A qualitative approach was employed, including semi-structured interviews, focus groups and document analysis of AI and human translations of Saudi cultural terms. Findings reveal that while AI tools improve translation speed and efficiency, they often fail to capture emotional tone and cultural context, necessitating human refinement. UTAUT highlighted usability factors and adoption barriers, while CAT exposed AI’s limitations in handling culturally embedded language. The study concludes that AI should complement, not replace, human translators in culturally significant contexts. It recommends hybrid workflows, enhanced training data, translator involvement in AI design and improved post-editing infrastructure. These findings inform strategies for culturally competent AI integration in alignment with Saudi Arabia’s socio-cultural and technological goals.
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