Artificial intelligence and the changing architecture of work: skill adaptation, occupational restructuring and the distribution of labor-market opportunities
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Abstract
Artificial intelligence is transforming labor markets by modifying the structure of tasks, the demand for skills, and the distribution of employment opportunities. This paper examines the relationship between artificial intelligence, workforce skill transformation, and labor-market inequalities by synthesizing recent contributions on automation, human–AI complementarity, digital capabilities, occupational restructuring, and institutional adjustment. The literature shows that AI can generate productivity gains, support the creation of new tasks, and improve worker performance when technological systems complement human capabilities. However, these benefits are unevenly distributed. Workers performing routine or readily automatable tasks may face displacement, wage pressure, or occupational downgrading, while individuals possessing technological, cognitive, social, and organizational skills are generally better positioned to benefit from technological change. Inequalities are also shaped by age, gender, geography, employment status, informality, and access to training. Organizational choices further influence whether AI strengthens worker autonomy or increases algorithmic control. The paper concludes that the distributional consequences of AI depend not only on technological characteristics but also on education, continuous reskilling, labor mobility, social protection, formalization, and institutional quality. An inclusive AI transition therefore requires policies that combine innovation with human-capital development and mechanisms capable of broadening access to the productivity gains generated by technological transformation
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