Artificial intelligence adoption: productivity effects and supporting policies

Luigi Bellomarini (), Fabio Bertolotti (), Luca Citino (), Maria Giulia Cassinis (), Francesco D'Amuri (), Silvia Del Prete (), Sara Formai (), Litterio Mirenda, Massimiliano Rigon () and Anna Russo Russo ()
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Luigi Bellomarini: Bank of Italy
Fabio Bertolotti: Bank of Italy
Luca Citino: Bank of Italy
Maria Giulia Cassinis: Bank of Italy
Francesco D'Amuri: Bank of Italy
Silvia Del Prete: Bank of Italy
Sara Formai: Bank of Italy
Massimiliano Rigon: Bank of Italy
Anna Russo Russo: Bank of Italy

No 1009, Questioni di Economia e Finanza (Occasional Papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: In Italy, the share of firms adopting artificial intelligence technologies is growing but remains below the European average. Long-run estimates suggest that the diffusion of this technology could raise productivity by 0.2 - 1.1 percentage points per year over the next decade, depending on the speed and depth of adoption. In the short run, however, no significant effects on firm-level productivity are apparent yet, despite documented gains at the level of individual tasks: this outcome is consistent with the literature, in which aggregate benefits only materialize after substantial organizational adjustments. The paper identifies the main barriers to adoption and the conditions that justify public intervention. Drawing on an analysis of the policies adopted in more advanced countries, it highlights the need for a coherent strategy that, rather than relying on poorly targeted subsidies, supports firms through the adoption process, fosters the supply of applications by encouraging the development of specialized providers, and invests in enabling factors: regulatory certainty, data sharing, and ease of access to computing infrastructure.

Keywords: artificial intelligence; technology adoption; productivity; firm performance; industrial policy (search for similar items in EconPapers)
JEL-codes: D24 O33 O38 O47 (search for similar items in EconPapers)
Date: 2026-06
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