Mapping Generative AI Exposure in Business and Economics Higher Education: Evidence from Romanian Public Universities
Abstract
Generative Artificial Intelligence (GenAI) is reshaping labour markets and creating new challenges for higher education. This study develops an analytical framework for assessing the occupational exposure associated with university study programmes. The framework maps university qualifications to occupational profiles and applies the ILO Global Occupational Exposure Index to estimate the occupational exposure of future graduates. A database was developed by integrating information from the Romanian National Qualifications Register (RNCIS), official data on enrolment capacity, COR, ISCO-08 and occupational exposure data from the ILO Global Occupational Exposure Index. The database covers 263 Business and Economics Bachelor’s programmes and 27,690 potential graduates from Romanian public universities. The findings show that 66.9% of potential graduates are associated with occupations characterised by high exposure to Generative AI, while no study programmes are linked to occupations classified as Not Exposed, Minimal Exposure or Gradient 1. The study provides the first systematic assessment of occupational exposure associated with university study programmes through the analysis of Business and Economics Bachelor’s programmes in Romanian public universities. The proposed framework is transparent, replicable and can be applied to other ISCED fields and national higher education systems.
© 2026 Silvia Mărginean, Ramona Orăștean, Raluca Sava, published by Lucian Blaga University of Sibiu
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.