Contenuto in:
Capitolo

Advancing AI competencies: Building strategies for capability building in national statistical institutes

  • Daniela Pagliuca
  • Gianmarco Schiesaro

The Italian National Institute of Statistics (Istat) recognizes training in Artificial Intelligence (AI) as a strategic component of its digital transformation, supporting a broad cultural shift. Since 2022, it has implemented a comprehensive training program, including courses on Machine Learning, Deep Learning, and Python, alongside AI literacy modules delivered through blended learning methods. Particular attention is paid to alignment with the European regulatory framework, notably the AI Act. At the same time, the Institute aims to establish itself as a learning organization, fostering continuous and widespread learning based on interaction, the valorization of internal expertise, and the development of a resilient training ecosystem. To this end, Communities of Practice (CoPs) play a key role as collaborative spaces for knowledge sharing and support for innovation processes. In this context, the strategy focuses on several key areas, including: • Structured training: A coherent institutional offer comprising courses, webinars, and masterclasses on emerging topics such as generative AI and virtual assistants, complemented by external learning resources. • Innovative learning approaches: The implementation of flexible and accessible formats, including microlearning modules and educational podcasts, designed to accommodate diverse learning preferences and busy schedules. • Cultural change: A medium-to-long-term pathway aimed at developing transferable skills—such as critical thinking, systems thinking, and complexity management—while promoting an organizational mindset transformation that is mindful of intergenerational differences. The ultimate goal is to create a dynamic environment that fosters professional growth, continuous learning, and knowledge sharing.

  • Keywords:
  • Artificial Intelligence,
  • AI literacy,
  • Capability building,
  • Learning Organization,
  • Communities of Practice,
+ Mostra di più

Daniela Pagliuca

ISTAT, Italian National Institute of Statistics, Italy

Gianmarco Schiesaro

ISTAT, Italian National Institute of Statistics, Italy

  1. Davenport, E., Hall, H. (2005). Organizational knowledge and communities of practice. Annual Review of Information Science and Technology (ARIST), 36, pp. 170-227. DOI: 10.1002/aris.1440360105
  2. Hemmasi, M., Csanda, C.M. (2009). The effectiveness of communities of practice: An empirical study. Journal of Managerial Issues, 21, pp. 262-279. DOI: 10.48009/2_iis_2009_242-248
  3. Hughes, J., Jewson, N., Unwin, L. (2007). Communities of Practice: Critical Perspectives. Routledge, New York, (USA).
  4. Laland, K.N. (2004). Social learning strategies. Learning & Behavior, 32(1), pp. 4-14. DOI: 10.3758/bf03196002
  5. Lave, J., Wenger, E. (1991). Situated Learning: Legitimate Peripheral Participation. Cambridge University Press, Cambridge, (UK). DOI: 10.2307/2804509
  6. Letardi, S., Pace, S., Pagliuca, D., Prigiobbe, V. (2025). Adopting AI at Istat: Building an inclusive governance framework, in Generative AI and Official Statistics Workshop 2025. Proceedings of the Conference of European Statisticians, United Nations Economic Commission for Europe, Geneva, (CH), 12-14 May 2025.
  7. Li, L.C., Grimshaw, J.M., Nielsen, C., Judd, M., Coyte, P.C., Graham, I.D. (2009). Evolution of Wenger's concept of community of practice. Implementation Science, 4, pp. 11. DOI: 10.1186/1748-5908-4-11
  8. Monib, W.K., Qazi, A., Apong, R.A. (2025). Microlearning beyond boundaries: A systematic review and a novel framework for improving learning outcomes. Heliyon, 11(2). DOI: 10.1016/j.heliyon.2024.e41413
  9. Morandini, S., Fraboni, F., De Angelis, M., Puzzo, G., Giusino, D., Pietrantoni, L. (2023). The impact of artificial intelligence on workers' skills: Upskilling and reskilling in organisations. Informing Science, The International Journal of an Emerging Transdiscipline, 26, pp. 039-068. DOI: 10.28945/5078
  10. Nigam, P., Chavla, P. (2024). Agile competencies—the way to manage talent in an agile organisation, in N. Sushil Rani, R. Joshi (eds.). Flexibility, Resilience and Sustainability, Springer Nature Singapore, Singapore, (SG), pp. 287-299. DOI: 10.1007/978-981-99-9550-9_16
PDF
  • Anno di pubblicazione: 2026
  • Pagine: 309-314

XML
  • Anno di pubblicazione: 2026

Informazioni sul capitolo

Titolo del capitolo

Advancing AI competencies: Building strategies for capability building in national statistical institutes

Autori

Daniela Pagliuca, Gianmarco Schiesaro

Lingua

Inglese

DOI

10.36253/979-12-215-1062-1.54

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

Editore

Firenze University Press

DOI

10.36253/979-12-215-1062-1

ISBN Print

979-12-215-1061-4

eISBN (pdf)

979-12-215-1062-1

eISBN (xml)

979-12-215-1063-8

Collana

Applied Statistics Series

0

Download dei libri

0

Visualizzazioni

Salva la citazione

1.528

Libri in accesso aperto

in catalogo

3.744

Capitoli di Libri

6.674.567

Download dei libri

5.994

Autori

da 1219 Istituzioni e centri di ricerca

di 67 Nazioni

83

scientific boards

da 416 Istituzioni e centri di ricerca

di 46 Nazioni

1.439

I referee

da 400 Istituzioni e centri di ricerca

di 41 Nazioni