Methodology for Calculating the Human Capital Vulnerability to AI Index

The rapid proliferation of artificial intelligence (AI) technologies is transforming the role of human capital in value creation, generating both new developmental opportunities and substantial risks. This study addresses the following research question: how can human capital vulnerability to AI be systematically measured and compared across countries? The purpose of this study is to develop a methodology for calculating the index for human capital vulnerability to AI and to validate it through cross-country comparative analysis to overcome analytical fragmentation in examining the consequences of AI diffusion. A human capital vulnerability to AI index is constructed as a composite indicator encompassing five interrelated dimensions: national technological readiness, human capital adaptability, institutional protective capacity, structural labour market vulnerability, and migration-related vulnerability. Twenty-four indicators are normalised using the min–max method; subindex weights are determined via principal component analysis. The framework is validated on a sample of six countries—Germany, France, Finland, Estonia, Poland, and Ukraine—selected through cluster analysis, drawing on data from the OECD, Eurostat, the State Statistics Service of Ukraine, and Oxford Insights. Results reveal substantial cross-country heterogeneity, ranging from Finland’s low vulnerability, underpinned by strong institutional readiness, to Ukraine’s critical vulnerability, driven by compounded structural, institutional, labour market, and migration constraints, with Germany, France, Estonia, and Poland occupying intermediate positions shaped by labour market exposure, migration pressures, and limited technological readiness, respectively. The proposed methodology integrates the precision of multivariate statistical tools with conceptual rigour, enabling reliable and interpretable cross-country differentiation of human capital vulnerability under AI-driven transformation for forecasting labour market changes and shaping targeted retraining and social protection policies.