STATISTICAL METHODS OF PERSONNEL MANAGEMENT IN AN ORGANIZATION: INTEGRATION OF ARTIFICIAL INTELLIGENCE AND DEVELOPMENT FORECASTS

UDC 37
DOI: 10.36871/ek.up.p.r.2025.06.08.005

Authors

Dmitry B. Khalemsky
Nadezda P. Tishkina,
Moscow Financial and Industrial University Synergy University

Abstract

The article discusses modern approaches to the management of an organization’s personnel with an emphasis on the integration of statistical methods and artificial intelligence. It is shown that effective management decisions cannot be made without a systematic analysis of large amounts of data on employees, including both structured and unstructured information. The main statistical tools used to evaluate and predict personnel processes are described: distribution analysis, hypothesis testing, and assessment of the relationships between personnel indicators. Special attention is paid to the role of artificial intelligence in automating HR processes, identifying hidden patterns, and personalizing the management of employee competencies. The article presents the prospects for the development of digital HR technologies, including the creation of corporate neural networks and increased requirements for information security. It is concluded that the integration of statistical methods and AI ensures the scientific validity of HR

Keywords

Human resources management, statistical methods, artificial intelligence, big data, HR analytics, hypothesis testing, normal distribution, corporate data, forecasting, digitalization of HR, employee competencies, automation of HR processes, neural networks, information security