This academic article examines the multifaceted impact of artificial intelligence technologies on contemporary philology. Traditional methods of text analysis, which rely on manual labor and the researcher’s subjective interpretation, are now complemented by powerful tools from computational linguistics, deep learning, and large language models. The paper analyzes how natural language processing (NLP) algorithms are transforming approaches to text attribution, semantic analysis, and comparative-historical linguistics. Particular attention is paid to the automation of the process of deciphering ancient manuscripts and identifying hidden intertextual connections in fiction. The results of the study demonstrate that the synergy between AI and classical philology leads to the formation of a new interdisciplinary paradigm-digital philology. The article justifies the need to adapt educational programs to train specialists who are proficient in both methods of literary analysis and skills in working with AI-based software. The scientific novelty lies in the systematization of relevant case studies on the application of neural networks in the study of language structure and textual poetics.
Nigora Jumanazarovna Bozorova (2026) studied this question.