EU-funded investment in Artificial Intelligence and regional specialization

Anabela Marques Santos (), Francesco Molica () and Carlos Torrecilla Salinas ()
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Anabela Marques Santos: European Commission, Joint Research Centre, Sevilla, Spain
Francesco Molica: European Commission, Joint Research Centre, Brussels, Belgium
Carlos Torrecilla Salinas: European Commission, Joint Research Centre, Sevilla, Spain

No 181, GEE Papers from Gabinete de Estratégia e Estudos, Ministério da Economia

Abstract: Artificial Intelligence (AI) is seen as a disruptive and transformative technology with the potential to impact on all societal aspects, but particularly on competitiveness and growth. While its development and use has grown exponentially over the last decade, its uptake between and within countries is very heterogeneous. The paper assesses the geographical distribution at NUTS2-level of EU-funded investments related to AI during the programming period 2014-2020. It also examines the relationship between this specialization pattern and regional characteristics using a spatial autoregressive model. Such an analysis provides a first look at the geography of public investment in AI in Europe, which has never been done before. Results show that in the period 2014-2020, around 8 billion EUR of EU funds were targeted for AI investments in the European regions. More developed regions have a higher specialization in AI EU-funded investments. This specialization also generates spillover effects that enhance similar specialization patterns in neighboring regions. AI-related investments are more concentrated in regions with a higher concentration of ICT activities and that are more innovative, highlighting the importance of agglomeration effects. Regions that have selected AI as an innovation priority for their Smart Specialization Strategies are also more likely to have a higher funding specialization in AI. Such findings are very relevant for policymakers as they show that AI-related investments are already highly spatially concentrated. This highlights the importance for less-developed regions to keep accessing to sufficient amounts of pre-allocated cohesion funds and to devote them for AI-related opportunities in the future.

Keywords: Artificial intelligence; Public subsidy; Territorial specialization; Europe (search for similar items in EconPapers)
JEL-codes: O31 O52 R12 R58 (search for similar items in EconPapers)
Date: 2024-07, Revised 2024-07
New Economics Papers: this item is included in nep-ain, nep-eec, nep-eur, nep-geo, nep-ict, nep-ino, nep-sbm, nep-tid and nep-ure
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https://www.gee.gov.pt//RePEc/WorkingPapers/GEE_PAPERS_181.pdf First version, 2024 (application/pdf)

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