Occupational Convergence or Divergence? Mapping Labor Market Structural Shifts Driven by AI Penetration

Artificial intelligence (AI) is rapidly becoming a defining feature of contemporary labor markets, yet it remains unclear whether its diffusion is producing a common set of competencies across occupations or deepening occupational divisions. In this study, we investigate how AI related skill demand is reshaping labor market structure using large-scale online vacancy data from ten countries spanning the Global North and Global South. Combining natural language processing and a large language model with multilevel bipartite network analysis, we map the relationships between occupations, required skills, and career stages in the emerging AI economy. We find that AI demand is overwhelmingly concentrated within a narrow technical core, with approximately three quarters to four fifths of AI related vacancies located in STEM occupations across all countries. At the same time, AI intensive jobs share a remarkable focus on Python, SQL, machine learning, and data analysis, generating convergence among highly exposed occupations. Interestingly, this convergence does not extend across the wider labor market.

Introduction. The increasing penetration of artificial intelligence (AI) is transforming the nature of work across a wide range of occupational domains. As organizations integrate AI into production processes, decision making systems, and service delivery, workers are increasingly expected to interact with AI enabled tools and technologies in their daily professional activities. Consequently, labor markets are experiencing a gradual reconfiguration of skill requirements with AI related competencies becoming more visible in job advertisements and recruitment practices. While the diffusion of AI has generated considerable discussion regarding its implications for productivity and employment, less attention has been devoted to understanding how AI related skill demands are reshaping the broader structure of occupations. In particular, an important question remains whether the growing demand for AI competencies is fostering equally similarly across occupations or the required new skills are unequally distributed across fields.

Discussion / Conclusion. According to our results, AI is not homogenizing the labor market. It is splitting it at different forces and multiple scales. The emergence of AI related skill requirements is producing neither a general convergence of occupations nor a simple intensification of specialization. Instead, it is reorganizing labor markets into a bifurcated structure. Within occupations already exposed to AI, demand converges on a compact and highly transferable core of data competencies that recurs across sectors of this group, countries, and career stages. Beyond this AI exposed core, however, convergence remains limited, concentrated within a narrow technical stratum, most strongly expressed at the point of labor market entry, and mostly reveals divergence of occupations. AI is therefore generating convergence and divergence simultaneously as convergence among technologically intensive occupations faces divergence between those occupations and the wider labor market. Furthermore, this bifurcation extends existing accounts of technological change and labor market polarization.