ALGORITHMIC MANAGEMENT IN HUMAN RESOURCE MANAGEMENT IN UZBEKISTAN

Abstract

Abstract. Algorithmic management is becoming an important dimension of contemporary human resource management because digital systems can process large volumes of workforce data, support managerial decisions and automate selected HR activities. This article examines the emerging role of algorithmic management in Uzbekistan, with particular attention to public-sector human resource management and the country’s broader digital and artificial intelligence reforms. The study combines a review of academic literature on algorithmic HRM with analysis of Uzbekistan’s civil-service reform agenda, the ARGOS digital HR ecosystem, the national Artificial Intelligence Development Strategy until 2030 and recent government initiatives. The analysis focuses on recruitment and selection, algorithmic assessment, learning and development, and performance management. The findings indicate that Uzbekistan has established important digital foundations for algorithmic HR management, including online recruitment, electronic personnel administration, digital assessment and professional-development platforms. At the same time, publicly available evidence does not justify describing the entire Uzbek HR system as fully algorithmically managed. Rather, the country is moving from digital HR administration towards more data-driven and AI-supported management. The article identifies opportunities in faster processing, evidence-based workforce planning, personalised learning and performance analytics, while highlighting risks related to bias, explainability, privacy, surveillance and over-reliance on automated recommendations. It recommends human oversight, stronger data governance, regular algorithmic audits and AI literacy for HR professionals.