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Embracing gen AI: a comparison of Italian and US households

Author

Listed:
  • David Loschiavo
  • Olivier Armantier
  • Antonio Dalla Zuanna
  • Leonardo Gambacorta
  • Mirko Moscatelli
  • Ilaria Supino

Abstract

This paper explores the household adoption of Generative Artificial Intelligence (GenAI) in the United States and Italy, leveraging survey data to compare usage patterns, demographic influences, and employment sectoral composition effects. Our findings reveal higher adoption rates in the US, driven by socio-demographic differences between the two countries. Despite their lower usage of GenAI, Italians are more confident in its potential to improve their well-being and financial situation. Both Italian and US users tend to trust GenAI tools less than human-operated services, but Italians report greater relative trust in government and institutions when handling personal data with GenAI tools.

Suggested Citation

  • David Loschiavo & Olivier Armantier & Antonio Dalla Zuanna & Leonardo Gambacorta & Mirko Moscatelli & Ilaria Supino, 2026. "Embracing gen AI: a comparison of Italian and US households," BIS Working Papers 1322, Bank for International Settlements.
    • Handle: RePEc:bis:biswps:1322
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    References listed on IDEAS

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    1. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-1044, September.
    2. Barth, Erling & Davis, James C. & Freeman, Richard B. & McElheran, Kristina, 2023. "Twisting the demand curve: Digitalization and the older workforce," Journal of Econometrics, Elsevier, vol. 233(2), pages 443-467.
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    5. David Loschiavo & Mirko Moscatelli, 2025. "Adoption and expected impact of Generative AI: evidence from Italian households," Questioni di Economia e Finanza (Occasional Papers) 929, Bank of Italy, Economic Research and International Relations Area.
    6. Fabrizio Dell'Acqua & Charles Ayoubi & Hila Lifshitz & Raffaella Sadun & Ethan Mollick & Lilach Mollick & Yi Han & Jeff Goldman & Hari Nair & Stewart Taub & Karim Lakhani, 2025. "The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise," NBER Working Papers 33641, National Bureau of Economic Research, Inc.
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    Keywords

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    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • D10 - Microeconomics - - Household Behavior - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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