ARTIFICIAL INTELLIGENCE IN TRANSLATION: ANALYZING ITS INFLUENCE ON ACCURACY, EFFICIENCY, AND CULTURAL SENSITIVITY

Abstract

In recent years, artificial intelligence (AI) has significantly reshaped the field of translation, introducing advanced technologies that enable faster, more scalable, and cost-effective multilingual communication. At the forefront of this transformation is neural machine translation, a deep learning-based approach that has replaced traditional rule-based and statistical methods with systems capable of producing increasingly natural and fluent translations. This article investigates the impact of AI-driven translation tools on language services, highlighting their advantages in terms of speed, accessibility, and application across industries such as e-commerce, healthcare, education, and humanitarian services. However, despite these advancements, AI translation systems continue to face critical limitations, particularly in their ability to capture cultural nuance, context-specific meaning, and stylistic intent. Furthermore, ethical concerns regarding job displacement, data privacy, and algorithmic bias persist as key areas of debate. Drawing on case studies, recent developments, and expert perspectives, this article argues that while AI has become an indispensable asset in translation workflows, the role of human translators remains vital for ensuring quality, accuracy, and intercultural communication.