IDEAS home Printed from https://ideas.repec.org/p/bdi/opques/qef_929_25.html
   My bibliography  Save this paper

Adoption and expected impact of Generative AI: evidence from Italian households

Author

Listed:
  • David Loschiavo

    (Bank of Italy)

  • Mirko Moscatelli

    (Bank of Italy)

Abstract

Generative Artificial Intelligence (Gen AI) represents a revolutionary shift in the field of Artificial Intelligence. Its ability to solve complex cognitive tasks and to create original material may enhance productivity in a wide range of work activities. In this paper we use data from the Bank of Italy's Conjunctural Survey on Italian Households for the period between August and September 2024 to provide empirical evidence on the socio-demographic factors influencing Gen AI adoption, to assess the level of trust in AI-based services compared to human-managed alternatives, and to examine expectations regarding Gen AI's impact on the job market. Results indicate that a quarter of respondents used Gen AI tools in the 12 months preceding the survey, and 10 per cent used them at least once a week. Use of Gen AI was more common among men, younger respondents, and workers in the ITC, professional, and education sectors. Young workers and workers in the ITC sector also reported significantly higher expectations that Gen AI tools will increase their work productivity or provide them with new job opportunities.

Suggested Citation

  • 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.
    • Handle: RePEc:bdi:opques:qef_929_25
    as

    Download full text from publisher

    File URL: https://www.bancaditalia.it/pubblicazioni/qef/2025-0929/QEF_929_25.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mauro Cazzaniga & Ms. Florence Jaumotte & Longji Li & Mr. Giovanni Melina & Augustus J Panton & Carlo Pizzinelli & Emma J Rockall & Ms. Marina Mendes Tavares, 2024. "Gen-AI: Artificial Intelligence and the Future of Work," IMF Staff Discussion Notes 2024/001, International Monetary Fund.
    2. Aldasoro, Iñaki & Armantier, Olivier & Doerr, Sebastian & Gambacorta, Leonardo & Oliviero, Tommaso, 2024. "The gen AI gender gap," Economics Letters, Elsevier, vol. 241(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Raphael Auer & David Köpfer & Josef Švéda & Raphael A. Auer, 2024. "The Rise of Generative AI: Modelling Exposure, Substitution, and Inequality Effects on the US Labour Market," CESifo Working Paper Series 11410, CESifo.
    2. Yusuke Aoki & Joon Suk Park & Yuya Takada & Koji Takahashi, 2025. "Expecting job replacement by GenAI: effects on workers' economic outlook and behavior," BIS Working Papers 1269, Bank for International Settlements.
    3. Antonio Dalla Zuanna & Davide Dottori & Elena Gentili & Salvatore Lattanzio, 2024. "An assessment of occupational exposure to artificial intelligence in Italy," Questioni di Economia e Finanza (Occasional Papers) 878, Bank of Italy, Economic Research and International Relations Area.
    4. Gabriel Demombynes & Jorg Gero Langbein & Michael Weber, 2025. "The Exposure of Workers to Artificial Intelligence in Low- and Middle-Income Countries," Policy Research Working Paper Series 11057, The World Bank.
    5. Schrape, Jan-Felix, 2025. "Artificial intelligence and social action: A techno-sociological contextualization," Research Contributions to Organizational Sociology and Innovation Studies, SOI Discussion Papers 2025-03, University of Stuttgart, Institute for Social Sciences, Department of Organizational Sociology and Innovation Studies.
    6. Aldasoro, Iñaki & Armantier, Olivier & Doerr, Sebastian & Gambacorta, Leonardo & Oliviero, Tommaso, 2024. "The gen AI gender gap," Economics Letters, Elsevier, vol. 241(C).
    7. Alexandrov, Georgii A., 2025. "When does artificial intelligence replace process-based models in ecological modelling?," Ecological Modelling, Elsevier, vol. 499(C).

    More about this item

    Keywords

    generative artificial intelligence; households; job market; digital divide;
    All these keywords.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bdi:opques:qef_929_25. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bdigvit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.