Generative AI Practices, Literacy, and Divides: An Empirical Analysis in the Italian Context

• URL: http://arxiv.org/abs/2512.03671v1
• Date: Wed, 03 Dec 2025 11:01:28 GMT
• Title: Generative AI Practices, Literacy, and Divides: An Empirical Analysis in the Italian Context
• Authors: Beatrice Savoldi, Giuseppe Attanasio, Olga Gorodetskaya, Marta Marchiori Manerba, Elisa Bassignana, Silvia Casola, Matteo Negri, Tommaso Caselli, Luisa Bentivogli, Alan Ramponi, Arianna Muti, Nicoletta Balbo, Debora Nozza,
• Abstract summary: This study presents the first comprehensive empirical mapping of GenAI adoption, usage patterns, and literacy in Italy.<n>Our findings reveal widespread adoption for both work and personal use, including sensitive tasks like emotional support and medical advice.<n>We identify a significant gender divide where women are half as likely to adopt GenAI and use it less frequently than men.
• Score: 32.495879271249414
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rise of Artificial Intelligence (AI) language technologies, particularly generative AI (GenAI) chatbots accessible via conversational interfaces, is transforming digital interactions. While these tools hold societal promise, they also risk widening digital divides due to uneven adoption and low awareness of their limitations. This study presents the first comprehensive empirical mapping of GenAI adoption, usage patterns, and literacy in Italy, based on newly collected survey data from 1,906 Italian-speaking adults. Our findings reveal widespread adoption for both work and personal use, including sensitive tasks like emotional support and medical advice. Crucially, GenAI is supplanting other technologies to become a primary information source: this trend persists despite low user digital literacy, posing a risk as users struggle to recognize errors or misinformation. Moreover, we identify a significant gender divide -- particularly pronounced in older generations -- where women are half as likely to adopt GenAI and use it less frequently than men. While we find literacy to be a key predictor of adoption, it only partially explains this disparity, suggesting that other barriers are at play. Overall, our data provide granular insights into the multipurpose usage of GenAI, highlighting the dual need for targeted educational initiatives and further investigation into the underlying barriers to equitable participation that competence alone cannot explain.

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