Emerging AI Entrepreneurship Ecosystems in Europe: Are they geographically unbounded? – Alina Sorgner

Sprecherin

Alina Sorgner (John Cabot University, Rome; IfW Kiel; IZA Bonn)

Abstract

This paper investigates the regional distribution of firm-level AI technology adoption using a novel source of web-scraped data from websites of economically active firms in Europe. Using a narrow definition of AI adoption based on the importance of AI for a firm’s organizational identity, it is shown that AI adoption remains a very rare phenomenon in Europe occurring on average in 0.26 percent of all firms. Moreover, about half of all AI adopting firms are young startups that are no older than five years. While AI adopters are often based in highly dense urban areas, often in capital city metropolitan regions, regions with a high share of AI startups among all AI adopters are not necessarily big cities. Regional factors that are associated with the firm-level AI adoption are, for instance, regional demographics (e.g., lower median population age), regional socioeconomic characteristics (e.g., higher GDP per capita, higher total factor productivity (TFP)), regional digital economy (e.g., a higher share of employment in high-tech sectors and digital users), digital and physical infrastructure. Regional factors seem to play a less pronounced role for AI startups than for established AI adopters. Interestingly, the share of AI startups in all AI adopters is higher in regions with a significantly lower TFP. These results point toward emerging AI entrepreneurship ecosystems in Europe, for which geography plays a potentially different role compared to traditional entrepreneurship.

Raum

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