Balancing Innovation and Regulation: Comparative Approaches to AI-Driven Labour Market Planning in North Macedonia and China

The aim of this paper is to understand the differing approaches to planned labor between North Macedonia and China, with a focus on the role of artificial intelligence (AI) in their labor markets. As AI advanced, so did the concern about job displacement, particularly in those sectors in which automation and machine learning could possibly replace human workers. This study aims to analyze these risks that concern AI-driven job loss and the implications that could arise for the national economies. The central question that we are addressing is whether countries like North Macedonia and China should or could adopt better and stricter governmental policies on education and labor force planning to lower these risks, or whether a more liberal one, allowing flexible labor market dynamics, would be more beneficial in the long term.

On one hand, China has a structured approach to labor and education-strict quotas, state-directed economic plans, and a big focus on preparing the workforce and society for emerging technological fields like AI. On the other hand, North Macedonia still struggles to create quotas and regulatory frameworks to address these challenges, which leaves the labor market more flexible but also potentially vulnerable to disruptive technological changes.

With the analysis of the both countries' policies, this paper examines how North Macedonia and similar countries can learn from China's model, and create a balanced approach for labor market planning that has account for AI's impact. We also explore the role of education in preparing future generations for the future demands of an AI-driven economy and propose recommendations for policy reforms.