Against the backdrop of accelerating population decline and aging in many countries, artificial intelligence (AI) is rapidly reshaping labor market dynamics. This paper investigates the impact of AI diffusion on job replacement and net employment change in low-fertility societies. Using composite AI adoption metrics derived from OECD statistics, IFR reports, and national labor surveys, we build a multivariate linear regression model to quantify how AI penetration, total fertility rate, and education level affect labor outcomes. Empirical results show that AI penetration significantly increases job replacement risk, especially in routine-intensive sectors, while higher education levels and AI-related investment are associated with net job growth. The model achieves an average test R2 of approximately 0.8, indicating strong predictive performance and generalizability. This study highlights the dual role of AI as both a disruptive and enabling force in shrinking labor markets and provides quantitative evidence for policymakers to balance automation and employment resilience. The findings contribute to both AI economics and labor policy discourse under demographic transition.