Adoption and investment in AI across the euro area. Insights from harmonised firm-level data
Annalisa Ferrando,
Sara Lamboglia,
Judit Rariga and
Maurice Schmidt
No 395, Occasional Paper Series from European Central Bank
Abstract:
This paper explores the adoption of artificial intelligence (AI) technologies among euro area firms, using harmonised firm-level data from two dedicated modules of the Survey on the Access to Finance of Enterprises (SAFE) conducted in June and December 2025. Based on responses from around 6,000 firms across 12 euro area countries, the study examines AI adoption rates, drivers, barriers and economic implications. The findings suggest that AI diffusion among euro area firms is progressing rapidly but unevenly, with significant variation across countries and firm characteristics. Approximately 70% of firms report some level of AI use, but only 7% classify their adoption as significant. Adoption is highest in the Netherlands, Finland and Austria, and lowest in Italy and Ireland. Larger and younger firms, particularly in technology-intensive sectors, are leading adopters. Firms identify expected improvements in business processes as the main driver of adoption, while key barriers include skill shortages, data privacy concerns and system incompatibilities. Current AI use and investment are primarily financed through internal funds, complemented by grants and subsidised bank loans. AI adoption is positively associated with firm productivity, turnover growth, fixed investment and own selling price expectations, particularly among intensive users. Survey data show no evidence yet of aggregate labour shedding; instead, AI adoption is positively associated with employment growth. However, firms’ inflation expectations appear largely unaffected by current AI use. JEL Classification: C93, D22, E31, L25, O33
Keywords: artificial intelligence; firm-level survey data; inflation expectations; productivity (search for similar items in EconPapers)
Date: 2026-07
Note: 235236
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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbops:2026395
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