This study investigates how Artificial Intelligence (AI) influences the development of human competencies and contributes to workforce transformation. It addresses whether AI serves as an augmentation tool rather than a replacement threat, focusing on its predictive relationship with skill enhancement in diverse economic contexts. A quantitative approach was used, drawing on secondary panel data from the Global AI Index and the Human Capital Index. An Artificial Neural Network (ANN) model, featuring two hidden layers with 64 and 32 neurons, was developed to classify workforce competency outcomes. Key variables included AI adoption levels, labor interaction, and training infrastructure readiness. The ANN model achieved 80% accuracy in predicting competency development, with higher precision and recall for regions actively integrating AI into labor systems. The analysis revealed that such regions show distinct patterns of human capital improvement, driven by personalized learning, adaptive feedback, and flexible task design enabled by AI. The findings suggest that AI adoption acts as an enabler of workforce resilience and digital transformation. The study provides empirical evidence supporting the integration of AI into national upskilling strategies and organizational training agendas to foster inclusive, future-ready labor markets.
Arshad et al. (Mon,) studied this question.
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