Investigating The Scientific Focus On Artificial Intelligence'S Potential Impact On Labor Market

The pace of technological development, marked by its inexorable character, drives scientific research to continuously assess its economic impact. Research on the present and future effects materializes in an increasing volume of publications, the technological evolution bringing to the fore significant aspects of change, with increasingly evident accents of convergence towards the importance of researching the impact of technological evolution, especially artificial intelligence, on the labor market. Automation anxiety is the initial condition present in the labor market; the direction of technological development, and especially its direction, can influence the final impact. The widespread application of artificial intelligence, owing to its general applicability combined with the rapid advancement of specific technologies, sets the stage for significant economic and social transformation. Ongoing analysis of developmental stages and their potential impacts is essential to propose appropriate directing or regulatory measures. The purpose of this article is to capture the intensity and major concerns of the existing research on this topic at the global and national levels and to provide an overview and a recommendation for the selection of the literature for those who intend to research the relationship between technological development and the labor market. This article aims to identify the types of approach, the relevant topics, and the convergences towards possible clusters, along with the measurement of specific quantitative indicators: the number of publications per year, by authors, institutions, and countries. A bibliometric study was used as the research method. By analyzing the scientific literature based on quantitative indicators, this research captures the structure and dynamics of scientific research in this field. Measuring the impact and influence of scientific papers, identifying research trends, collaborative networks, and mapping clusters provide an overview of the evolution of the research field.