Abstract

As Artificial Intelligence (AI) increasingly reshapes labor markets and skill requirements, National Statistical Offices (NSOs) face growing pressure to modernize traditional statistical frameworks while preserving international comparability. This paper proposes a forward-looking approach for enhancing the ISCO-08 occupational classification to ensure its continued relevance in capturing emerging occupations and augmented tasks driven by generative AI and automation.
The study emphasizes the strategic importance of integrating occupational statistics with labor market, education, and demographic data within a unified analytical framework. Aligned with the United Nations Statistical Commission’s vision for an Integrated Demographic and Social Statistics Framework, this approach enables a more comprehensive understanding of human capital dynamics across population groups. Methodologically, the paper introduces a proposed “AI-Readiness and Skills Module” designed for inclusion within national Labor Force Surveys (LFS). Rather than replacing existing international standards, the module serves as a complementary extension that supports systematic monitoring of skill evolution, task transformation, and technology adoption, disaggregated by key demographic and socio-economic characteristics.
The paper argues that such targeted and scalable enhancements are essential for strengthening the policy relevance of official labor statistics. By increasing the granularity and analytical depth of ISCO-based data, NSOs can provide robust evidence to support inclusive workforce planning, responsive vocational training policies, and Sustainable Development Goals (SDGs) related to decent work and economic growth. The proposed framework positions official statistics as a proactive instrument for guiding societies through the transition to an AI-enabled digital economy.