Problems and further development of artificial intelligence in the translation business

Abstract

The article describes systemic changes in the translation industry and university training of translators under the influence of neural network technologies, interpreting artificial intelligence not as an auxiliary tool but as a full-fledged factor restructuring the cognitive model of professional activity. The transition from the production of translation to its expert validation is examined, where post-editing, critical analysis of machine output, and risk management of the “technological illusion of competence,” particularly characteristic of novice specialists, become central. Based on a large corpus of translations of different functional styles and a comparison of the performance of neural network systems, students, and professionals, the heterogeneity of machine output quality is identified: alongside a noticeable advantage of AI in adhering to formal grammatical norms, an increased frequency of semantic failures and stylistic dissonances is recorded, potentially more dangerous for communication than superficial errors. It is shown that the post-editing mode can produce a pronounced synergistic effect in terms of overall error reduction; however, it simultaneously amplifies the influence of “machine syntax” on textual naturalness and requires targeted pedagogical interventions. The economic dimension of digitalization is revealed through an analysis of speed and cognitive load: for simple standardized texts, automation provides a multiple increase in productivity with a moderate rise in fatigue, whereas for complex materials acceleration proves limited and is accompanied by a spike in cognitive costs and an increase in the share of products requiring factual retranslation, which reduces the expected benefit. A significant result is the identification of a “technological pitfall”: among users without specialized training, the use of AI degrades quality and increases variability, whereas training in neural network architecture, prompt practices, and post-editing stabilizes outcomes and brings students closer to professional standards. The study shapes an understanding of the prospective role of the translator as an expert validator and architect of transcultural communication and substantiates the need to integrate linguistic, technological, and ethical competence into educational models and industry labor regulations.