Machine Translation (MT) has become an essential technology for multilingual communication, enabling people and organizations to overcome language barriers quickly and efficiently. Despite significant advances in Neural Machine Translation (NMT) and Artificial Intelligence (AI), machine translation systems still face challenges when dealing with ambiguity, idiomatic expressions, and cultural context. These linguistic features require contextual and cultural understanding that machines often struggle to achieve. This paper discusses the main difficulties associated with translating ambiguous language, idioms, and culturally specific content and examines current approaches used to improve translation quality.