Assessing artificial intelligence readiness in EU e-government: insights from factor and cluster analysis

Abstract

Artificial Intelligence is playing an increasingly central role in the transformation of public governance, offering new possibilities for more adaptive, responsive, and citizen-centric service delivery. However, the extent to which European Union member states are institutionally and societally prepared to adopt these technologies in the public sector remains insufficiently explored. This thesis addresses that gap by providing a comparative assessment of Artificial Intelligence readiness across the European Union. Using secondary data from Eurostat and the European Commission’s electronic Government Benchmark, the study applies exploratory factor analysis to identify two core dimensions: Digital Skills and Electronic Government Engagement, and Transparency and Electronic Government Service Availability. These dimensions serve as inputs for hierarchical and k-means clustering, which reveal six distinct profiles of readiness among member states. The findings uncover substantial disparities in both infrastructural and citizen-level preparedness, reflecting broader digital divides. Ultimately, the results highlight that successful Artificial Intelligence integration in public governance is contingent not only on technological infrastructure but also on inclusive, citizen-oriented strategies. This thesis contributes an empirical framework for understanding readiness, offering practical insights for policymakers aiming to ensure that AI-driven digital transformation advances equitably across the European public sector.