Presenting an Intelligent Policymaking Framework for Labor Market Regulation in the Era of AI-Based Automation
Keywords:
Intelligent Policymaking, Labor Market, Artificial Intelligence, Automation, Data-Driven Governance, Employment Sustainability, Digital EconomyAbstract
The present study aimed to develop an intelligent policymaking framework for regulating the labor market in the era of AI-based automation and to identify the factors influencing labor market sustainability. This study employed an applied exploratory mixed-method design. In the qualitative phase, semi-structured interviews were conducted with 18 experts in policymaking, digital economy, artificial intelligence, and human resource management in Tehran, Iran, and the data were analyzed using thematic analysis. In the quantitative phase, the statistical population included labor market experts, executive managers, university faculty members, and technology specialists, from whom 312 participants were selected through stratified random sampling. The data collection instrument was a researcher-made questionnaire developed based on the qualitative findings. Data analysis was conducted using SPSS-27 and Smart PLS-4 software through confirmatory factor analysis and structural equation modeling. The findings demonstrated that all dimensions of intelligent policymaking, including data-driven governance, adaptive regulation, future-oriented skill development, intelligent social protection, algorithmic employment monitoring, digital justice, and institutional flexibility, had significant positive effects on labor market sustainability. Among the variables, future-oriented skill development had the strongest impact on labor market sustainability. Furthermore, model fit indices including GOF=0.71, NFI=0.93, and SRMR=0.054 confirmed the satisfactory fit of the proposed model. The coefficient of determination for labor market sustainability was 0.68, indicating the strong explanatory power of the model. The results revealed that labor market regulation in the age of artificial intelligence requires an intelligent, data-driven, flexible, and multidimensional approach. Developing future-oriented skills, strengthening institutional capacity, expanding intelligent social protection systems, and utilizing data-based governance mechanisms can significantly enhance labor market resilience and sustainability. Moreover, successful policymaking in the digital economy depends on effective coordination among technological, social, educational, and economic dimensions.
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