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.
ISTAT, Italian National Institute of Statistics, Italy
ISTAT, Italian National Institute of Statistics, Italy
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
Licenza dei metadati
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
Licenza dei metadati
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