Publication Details
Abstract
This article examines the theoretical, methodological and practical aspects of digitalizing the assessment, selection and appointment of leadership personnel in the civil service and executive authorities of Uzbekistan. The study analyzes the advantages and risks of selecting candidates through the unified electronic database of the Civil Service Development Agency (hrm.argos.uz), artificial intelligence (AI) algorithms and Big Data analytics. Using systems analysis, comparative analysis, multi-criteria decision analysis (MCDA) and expert assessment, the views of Western, CIS and national management scholars are compared, and World Bank and national statistical data are discussed. The results indicate that digital platforms substantially shorten selection time, reduce administrative costs and limit the influence of subjective factors, while at the same time creating new risks of algorithmic bias, personal data leakage and cyberattacks. The author proposes a Digital Assessment Efficiency and Security Index (DAESI) that combines assessment accuracy, post-appointment performance, time and financial costs, and cyber and algorithmic risks into a single integral indicator, together with a five-stage architecture of AI-assisted selection and a risk management model. The article concludes with recommendations on introducing explainable AI, strengthening information security, establishing a digital appeal mechanism and developing the data literacy of managers.