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Adopting AI at Istat: Solutions and perspectives

  • Sara Letardi
  • Simona Pace
  • Marco Polizzi

Artificial Intelligence (AI) represents a highly transformative technology, capable not only of fostering innovation in official statistics but also of reshaping organizational processes and models. Due to its disruptive potential and the need to identify and mitigate associated risks, it is essential to establish a governance framework that is both robust and adaptable—capable of responding swiftly to ongoing developments. In this context, Istat has adopted an AI Governance Framework: a structured set of policies, procedures, and best practices developed through the synergistic collaboration of multiple organizational units. This framework is aligned with the risk levels defined by the AI Act and is designed to assess the impact of algorithms on citizens’ rights and interests, while maintaining a balance between innovation and public trust. The framework is built upon three interconnected pillars: • Innovation: promoting AI solutions that enhance operational efficiency and process quality; • Data & Rules: defining guidelines and best practices to ensure responsible and compliant use of AI; • People: fostering internal competencies through continuous training and targeted communication. The adopted model ensures adherence to ethical principles and the current regulatory framework, promoting a culture of responsible and informed AI use. In this regard, user-centricity is reflected in the development of use cases that are aligned with the Institute’s strategic objectives and regulatory context. In parallel, Istat is piloting governance monitoring tools aimed at ensuring effective oversight of AI applications, mitigating potential risks, and preserving the organization’s innovative capacity. The implementation plan for the framework includes a pilot phase to initiate activities, deploy monitoring tools, collect user feedback, and incorporate it into a continuous improvement process. In this work, we present the structure of the AI Governance Framework adopted by Istat, along with selected use cases and the tools necessary to support effective governance.

  • Keywords:
  • Artificial Intelligence,
  • Innovation,
  • Governance,
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Sara Letardi

ISTAT, Italian National Institute of Statistics, Italy

Simona Pace

ISTAT, Italian National Institute of Statistics, Italy

Marco Polizzi

ISTAT, Italian National Institute of Statistics, Italy

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  2. UNECE (2025). The Future of National Statistical Offices. https://unece.org/sites/default/files/2025-05/The%20Future%20of%20NSOs%2C%20A%20Call%20to%20Action%20-%20May%202025_0.pdf (page visited on 25th of July 2025)
  3. Batool, A., Didar Z., Muneera B. (2025). AI governance: A systematic literature review, AI and ethics. Onetrust, 5: pp. 3265–3279. DOI: 10.1007/s43681-024-00653-w
  4. EU (2024). Regulation (Eu) 2024/1689 of the European Parliament and of the Council, https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng (last accessed 01/03/2025
  5. Fedeli M., Pace S., Letardi S. (2025). What tools for a governance of AI solutions to support official statistics?, Italian Journal of Economic, Demographic and Statistical Studies, LXXIX(2), https://www.rieds-journal.org/rieds/article/view/390 (last accessed 10th of October 2025)
  6. Letardi S., Pace S., Pagliuca D., Prigiobbe V. (2025). Adopting AI at Istat: Building an Inclusive Governance Framework, UNECE, https://unece.org/sites/default/files/2025-05/GenAI2025_S4_Italy_Letardi_D.pdf (las accessed 10th of October 2025).
  7. MIM, Ministero dell’Istruzione e del Merito (2025). Linee guida per l’introduzione dell’Intelligenza Artificiale nelle Istituzioni scolastiche, (https://www.mim.gov.it/documents/20182/0/MIM_Linee+guida+IA+nella+Scuola_09_08_20(25-signed.pdf/b70fdc45-4b75-1f7e-73bf-eab12989b928?t=1756468797694 (last accessed 10th of October 2025)
  8. UNECE HLGMOS (2024). Gen AI For Official Statistics_Mitigating and Monitoring, published on-line on https://unece.org/statistics/documents/2024/Gen-AI-OS-Mitigating-and-Monitoring last accessed 09/03/2025
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  • Anno di pubblicazione: 2026
  • Pagine: 255-260

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  • Anno di pubblicazione: 2026

Informazioni sul capitolo

Titolo del capitolo

Adopting AI at Istat: Solutions and perspectives

Autori

Sara Letardi, Simona Pace, Marco Polizzi

Lingua

Inglese

DOI

10.36253/979-12-215-1062-1.45

Opera sottoposta a peer review

Anno di pubblicazione

2026

Copyright

© 2026 Author(s)

Licenza d'uso

CC BY 4.0

Licenza dei metadati

CC0 1.0

Informazioni bibliografiche

Titolo del libro

Data, Statistics and AI for Well-Being of People and Organisations

Curatori

Luigi Fabbris, Alberto Franci, Pietro Renzi

Opera sottoposta a peer review

Numero di pagine

420

Anno di pubblicazione

2026

Copyright

© 2026 Author(s)

Licenza d'uso

CC BY 4.0

Licenza dei metadati

CC0 1.0

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Firenze University Press

DOI

10.36253/979-12-215-1062-1

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979-12-215-1061-4

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979-12-215-1062-1

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979-12-215-1063-8

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Applied Statistics Series

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