employee
Russian Federation
employee
doctoral candidate
Moscow, Russian Federation
UDC 001.51
UDC 009
UDC 338.984
This article examines the role of artificial intelligence technologies, particularly large language models, in achieving the strategic goal of the Bauman Moscow State Technical University Development Program—developing human resources. Based on an analysis of the university's target indicators and human capital management policy principles (development of corporate culture, development of human resources, and equality of opportunity), the need to integrate large language models into the processes of attracting, developing, motivating, and retaining talent is substantiated. The article proposes a concept for an architectural model of an intelligent human capital management system that enables the automation of HR processes, personalized employee development, intelligent mentoring support, and predictive analytics of HR risks. The contribution of the proposed solutions to achieving key indicators is demonstrated: a change in the distribution of faculty working time (research/academic work) from 10/60 to 35/35, an increase in the average salary of academic staff relative to the regional average from 200% to 250%, a reduction in the teaching load from 900 to 600 hours per year, an increase in the employee satisfaction index from 56.2% to 90%, and an increase in the share of young scientists (candidates and doctors of science) from 13% to 25% by 2030.
large language models, human resource management, digital transformation of higher education, Bauman Moscow State Technical University, University 4.0
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