employee
Russian Federation
employee
doctoral candidate
Moscow, Russian Federation
UDC 001.51
UDC 009
UDC 338.984
This article examines the challenges of improving the efficiency of administrative, managerial, and economic activities in the context of the digital transformation of higher education and the transition to the University 4.0 model. Based on an analysis of strategic documents from Bauman Moscow State Technical University, the article substantiates the need to use large language models (LLM) to automate routine administrative processes, optimize document flow, provide intelligent support for management decisions, and improve service quality. An architectural model for integrating LLM into the university management system is proposed, including document processing services, an intelligent employee assistant, analytical support, and interaction with external systems. The proposed model's contribution to achieving the university's development program targets is demonstrated, including increased digital maturity, a reduction in the share of administrative and managerial personnel, and increased employee satisfaction.
large language models, artificial intelligence, control automation, digital transformation, University 4.0, Bauman Moscow State Technical University
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