Hungary 2030: Structural Exposure of Administrative and Routine Occupations to AI

Magyarország 2030: Az adminisztratív és rutinszerű munkakörök automatizálhatósági kockázata (2026–2030). This Zenodo record provides a reproducible working paper and supporting materials that quantify the structural exposure of Hungarian occupations to AI-driven task automation. The contribution is a transparent four-component AI Exposure Index integrating: (T) technical automatability, (R) routine intensity, (K) creativity requirement, and (S) social interaction requirement, combined with a Hungary-specific sector correction factor (M_sector). The methodology supports two execution modes: (i) an open-data pipeline using only publicly accessible sources and (ii) an enhanced pipeline that can incorporate licensed microdata (KSH and OECD PIAAC). The record documents data sources, schemas, and a configuration-driven workflow to enable replication and versioned updates. Key outputs include: (1) an occupation-level exposure ranking, (2) an “impact potential” ranking (exposure × employment headcount), and (3) sector and regional summary indicators when enriched inputs are available. The index measures structural exposure (relative risk), not a deterministic prediction of job loss. License: CC BY 4.0Primary DOI: https://doi.org/10.5281/zenodo.18825788