The emergence of artificial intelligence agents as a trend is creating a need for the implementation of digital consultants based on large-scale language models (LLMs) in various fields. In the evolving educational landscape, the introduction of AI agents in this field addresses a number of pressing issues, including tailoring instruction to individual abilities, reducing teacher workload, and promoting inclusive learning. This article provides a comprehensive review of research papers from the past 15 years, drawing on a comprehensive set of leading academic databases in this field. It identifies influential authors, priority subject areas, and key research areas.

The study methodology is based on a bibliometric analysis of 1,362 articles selected from the Web of Science database for 2010-2025, designed for network visualization and cluster analysis using VOSviewer software and the R programming language.

This bibliometric analysis mapped the intellectual landscape of scientific literature on the topic of digital consultants in education based on large-scale language models. This study provides valuable insights for researchers seeking to optimize LLM-based digital assistants. The results showed that the primary focus in this area is on aspects such as improving the privatized learning and decision-making systems in educational institutions and streamlining administrative management operations. However, issues such as the long-term impact of digital assistants, scalability, data privacy, ethical issues, and the need for robust intelligent management systems still require further study.