The rapid development of artificial intelligence has significantly influenced contemporary linguistic research, particularly in the field of automated text analysis. While AI-based tools are increasingly applied to literary texts, their effectiveness across different language systems remains insufficiently explored. This article investigates the potential and limitations of artificial intelligence in conducting linguistic analysis of literary texts belonging to distinct language systems, including analytical, inflectional, and agglutinative languages. The study focuses on lexical, morphological, syntactic, and semantic levels of analysis, with special attention to culturally embedded meanings characteristic of literary discourse. By comparing AI-generated analyses across languages with differing grammatical structures, the research reveals systematic discrepancies in accuracy and interpretative depth. The findings demonstrate that although artificial intelligence can efficiently process surface-level linguistic features, its performance is uneven across language systems and remains limited in addressing morphological complexity and cultural semantics. The study argues that AI should be regarded as a supplementary analytical tool rather than a substitute for traditional philological analysis.
Aisuluu Lema (2026) studied this question.