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Government Artificial Intelligence readiness and brain drain: influencing factors and spatial effects in the European Union member states

    Iulia Cristina Iuga Affiliation
    ; Adela Socol Affiliation

Abstract

In the swiftly advancing field of Artificial Intelligence (AI), a field where every country aims to keep pace, significant disparities are observed in how different nations adopt AI. This study explores the deep, yet insufficiently studied, effects of AI on societal, economic, and environmental aspects. It particularly examines how brain drain influences governmental AI implementation capabilities, addressing a gap in existing literature. The study investigates the interplay between government AI implementation and brain drain, factoring in macroeconomic conditions, governance quality, educational levels, and R&D efforts. Utilizing 2022 data from European Union countries, the research employs instrumental-variables regressions (2SLS and LIML) to counteract endogeneity and uses clustering methods for categorizing countries based on their government AI levels, alongside spatial analysis to detect cross-national spillovers and interactions. The findings reveal brain drain’s detrimental effect on governmental AI preparedness, highlight clustering tendencies, and identify spatial interdependencies. This paper underscores the need for strategic policy-making and institutional reforms to bolster government AI capabilities. It advocates for a paradigm shift in government frameworks post-New Public Management era, tailored to the new challenges posed by AI. The research, however, is limited to a single year and region, with constraints on data availability and indicator breadth.

Keyword : government AI readiness, brain drain, government expenditure, spatial effects, spillover effects, human capital

How to Cite
Iuga, I. C., & Socol, A. (2024). Government Artificial Intelligence readiness and brain drain: influencing factors and spatial effects in the European Union member states. Journal of Business Economics and Management, 25(2), 268–296. https://doi.org/10.3846/jbem.2024.21136
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Apr 4, 2024
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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