Artificial Intelligence in Translation: Technologies, Implications, and Future Directions

The integration of artificial intelligence into translation has significantly transformed linguistic mediation, multilingual communication, and professional translation practice. This article examines the technological foundations, practical applications, limitations, ethical concerns, and future directions of AI-powered translation systems. The study focuses particularly on neural machine translation, transformer-based architectures, attention mechanisms, multilingual modeling, and human-AI collaboration. The findings show that AI translation improves speed, scalability, accessibility, and cost efficiency in global communication. However, it still faces serious challenges in translating idioms, humor, figurative language, culturally specific meanings, legal and medical texts, and low-resource languages. Ethical issues such as bias, privacy, data security, and overreliance on automated systems also remain significant.