Artificial Intelligence (AI) has increasingly transformed translation practices across professional, academic, and industrial domains. Consequently, this study investigates the impact of AI on translation efficiency, translation quality, and translator roles, with particular focus on neural machine translation (NMT) and computer-assisted translation (CAT) tools. Using a mixed-methods approach that includes a literature review, survey of professional translators, and comparative analysis, the study demonstrates that AI enhances speed, consistency, and terminological accuracy, particularly in technical and repetitive translation tasks. Nevertheless, human oversight remains essential for idiomatic expressions, cultural nuances, and stylistic refinement. Therefore, the study emphasizes the emergence of a hybrid translation model that integrates AI tools with human expertise, ensuring both efficiency and quality.

Artificial Intelligence, Machine Translation, Neural Networks

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