ARTIFICIAL INTELLIGENCE AND DATA SCIENCE AS COMPLEMENTARY FORCES: A COMPARATIVE STUDY OF WORKFORCE TRANSFORMATION IN UZBEKISTAN AND SOUTH KOREA

Abstract

Artificial intelligence and data science are often discussed through the lens of job replacement, yet their relationship is more accurately understood as complementary. This article examines how artificial intelligence supports data science by automating repetitive tasks, improving analytical speed, assisting predictive modeling, and enabling data professionals to focus on interpretation, decision-making, and strategic problem-solving. The study compares Uzbekistan and South Korea to show how this relationship develops in two different economic and technological contexts. Uzbekistan is analyzed as an emerging digital economy where demand for data-related skills is gradually increasing across sectors such as finance, telecommunications, education, public administration, and business services. South Korea is examined as a technologically advanced economy with stronger digital infrastructure, broader AI adoption, and a more mature labor market for data science and artificial intelligence specialists. Using a comparative analytical approach based on secondary data, academic literature, policy reports, and labor market indicators, the article explores how AI integration transforms the role of data scientists rather than eliminating it. The findings suggest that AI reduces the time spent on technical and repetitive processes, while increasing the importance of human skills such as critical thinking, domain knowledge, ethical judgment, and business interpretation. The article concludes that the future of data science depends not on competition between humans and AI, but on the ability of professionals, universities, companies, and governments to build AI-supported data competencies.