Abstract
The rapid adoption of Artificial Intelligence (AI) is transforming global labor markets and redefining the nature of work in the digital economy. AI-driven technologies are increasingly being integrated across industries, enhancing operational efficiency, innovation, and productivity while simultaneously raising concerns about job displacement, skill obsolescence, and workforce adaptability. This study examines the relationships among AI adoption, workforce transformation, skill development, labor market outcomes, and economic productivity. A quantitative cross-sectional research design was employed, collecting data from 487 respondents across developed and developing economies. The data were analyzed using Structural Equation Modeling (SEM) with SmartPLS 4.0. The conceptual framework was grounded in Technology Acceptance Theory, Human Capital Theory, Skill-Biased Technological Change Theory, and Innovation Diffusion Theory. The findings reveal that AI adoption significantly enhances workforce transformation (β = 0.512, p < 0.001), leading to improved skill development, labor market performance, and economic productivity. Human-AI collaboration and organizational readiness were found to strengthen these positive relationships. However, AI adoption also negatively affects perceived job security (β = −0.218, p = 0.001), indicating the need for proactive workforce policies. The study highlights the importance of reskilling initiatives, inclusive AI governance, and effective human-machine collaboration in ensuring sustainable labor market transitions. These findings provide valuable insights for policymakers, organizations, and educational institutions seeking to maximize the benefits of AI while mitigating its socioeconomic challenges.
