Machine translation (MT) is still a huge challenge for both IT developers and users. From the beginning of machine translation, problems at the syntactic and semantic levels have been faced. Today despite progress in the development of MT, its systems still fail to recognise which synonym, collocation or word meaning should be used. Although mobile apps are very popular among users, errors in their translation output create misunderstandings. The paper deals with the analysis of machine translation of general everyday language in Lithuanian to English and English to Lithuanian language pairs. The results of the analysis show that more than two thirds of all the sentences were translated incorrectly, which means that there is a relatively small possibility that a mobile app will translate sentences correctly. The results are disappointing, because even after almost 70 years of MT research and improvement, researchers still cannot offer a system that would be able to translate with at least 50% correctness.