The Impact of Neural Networks on Labor Productivity in the Context of Demographic Decline: International and Russian Contexts

The study examines the potential of neural networks and artificial intelligence (AI) to mitigate the economic challenges posed by declining working-age populations globally. The aim of the study is to analyze specific instances of successful AI implementation that contribute to enhanced operational efficiency and labor productivity. The central thesis posits that AI can partially offset labor shortages and sustain stable economic growth. To support this argument, the Solow growth model is employed, wherein AI is conceptualized as a driving force behind technological progress, thereby fostering increased productivity. Particular attention is paid to the uneven distribution of AI technologies, noting that developed economies invest significantly more resources in AI research and development than developing nations. This disparity leads to a substantial gap in the realization of economic benefits. It is emphasized that, while this article demonstrates the potential of AI as a crucial instrument for addressing demographic challenges, it also highlights the increasingly relevant problem of inequality in access to advanced technologies and, consequently, the resulting disparities in the economic advantages they afford.