Artificial Intelligence Specialization in the European Union: Underexplored Role of the Periphery at NUTS-3 Level

TL;DR

This paper analyzes the distribution of AI research across European regions, revealing peripheral areas with high specialization and diverse citation impacts, highlighting regional disparities in AI research focus and visibility.

Contribution

It introduces a detailed bibliometric analysis of AI research distribution at the NUTS-3 regional level in Europe, emphasizing peripheral regions' roles.

Findings

Peripheral regions like Granada and Vilniaus apskritis show high AI specialization and citation impact.

Major metropolitan hubs dominate in publication volume but not necessarily in relative specialization.

Weak correlation between regional AI specialization and citation impact, indicating diverse regional research profiles.

Abstract

This study examines the distribution of Artificial Intelligence (AI) research across European NUTS-3 regions during the period 2015-2024. Using bibliometric data from Clarivate InCites and the Citation Topics classification system, we analyse two hierarchical thematic levels: Electrical Engineering, Electronics & Computer Science (Macro Citation Topic 4) and Artificial Intelligence & Machine Learning (Meso Citation Topic 4.61). Relative Specialization Index (RSI) and Relative Citation Impact (RCI) indicators are calculated for 781 European NUTS-3 regions. While major metropolitan hubs such as Paris, Warszawa, and Madrid dominate in absolute publication volume, the results reveal that the highest levels of relative AI specialization are concentrated in peripheral regions, particularly in Eastern Europe and Spain. Granada and Vilniaus apskritis stand out as regions combining high specialization with strong citation visibility. The analysis further suggests a weak relationship between regional specialization and citation impact, revealing multiple regional profiles, including highly specialized regions with limited citation visibility, highly visible regions with comparatively low specialization, and diversified scientific systems combining moderate specialization with strong citation impact. Fyn emerges as an extreme case of very high citation impact despite relatively low specialization.