Abstract
This study analyzes the socio-economic implications of artificial intelligence (AI) and generative AI (GenAI) deployment within global and national labor markets during the 2025–2026 transition period. Employing a secondary quantitative analysis of recent reports from the World Economic Forum (WEF), International Labor Organization (ILO), McKinsey, and PwC, alongside national data from Kazakhstan’s Center for Human Resources Development, the research evaluates the scale of structural labor transformation. Findings indicate a global net gain of 78 million jobs by 2030, masking a profound churn where 22% of employment undergoes structural change and 39% of current skills become obsolete. A critical dimension of this shift is the gendered risk of automation; women in high-income countries face a risk nearly three times higher than men due to their concentration in administrative roles. In Kazakhstan, the implementation of the «Law on AI» (2026) and the «Alem.AI» ecosystem marks a proactive state response to the potential transformation of 2.2 million workers. However, the study identifies the emergence of «Precariousness 2.0» a state of manufactured uncertainty characterized by a loss of professional autonomy and chronic anxiety. The research concludes that while the paradigm has shifted from «substitution» to «augmentation» the resulting «AI precariat» requires institutional interventions focusing on gender-sensitive retraining, regional R&D equity, and the mitigation of «cultural debt» to ensure social stability.