Translation plays a crucial role in facilitating global communication, enabling the exchange of knowledge, culture and commerce across linguistic boundaries in an increasingly interconnected world. This study examines the development of Computer Assisted Translation tools and Machine Translation systems from 2010 to 2025, focusing on their influence on translation quality, workflow dynamics and the evolving responsibilities of translators. Employing a qualitative document analysis approach, the research reviewed twenty peer reviewed academic sources obtained from Scopus, Web of Science, Google Scholar and Taylor and Francis Online. Search queries were refined using Boolean operators to ensure relevance to translation technology and professional practice. The findings reveal a clear progression from traditional translation memory-based systems to neural machine translation platforms that offer improved fluency but raise issues of semantic precision and reduced human agency. Translator roles have shifted significantly toward post editing and digital content management within collaborative and cloud enabled environments. While productivity has increased, concerns about cognitive fatigue, ethical accountability and professional deskilling have emerged. The study concludes that effective translation in the digital age depends on harmonizing machine efficiency with human insight and recommends updates in training, ethical guidelines and tool development to support this integration.
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