- Data, Statistics and AI for Well-Being of People and Organisations
- A cura di Luigi Fabbris, Alberto Franci, Pietro Renzi
The unequal geography of artificial intelligence: Labor market exposure and regional disparities in Italy
- Massimo Armenise
- Mauro Bruno
- Luigi De Iaco
- Marianna Mantuano
- Giulio Massacci
- © 2026 Author(s) |
- CC BY 4.0
- DOI: 10.36253/979-12-215-1062-1.8
The growing diffusion of Artificial Intelligence (AI) is reshaping production processes and organizational models across sectors, with far-reaching implications for employment structures, productivity dynamics, and socio-economic inequality. As AI continues to evolve, its impact on the labor market is inherently dual: while it complements and amplifies the productivity of high-skilled workers, it simultaneously threatens to displace tasks traditionally performed by lower-skilled occupations, particularly in routine-intensive jobs. This asymmetry risks reinforcing structural disparities within and across national labor markets, contributing to rising income inequality and regional divergence. Building on the methodology proposed by Webb (2019), this study develops an occupation-level measure of AI exposure in Italy. The indicator is derived by analyzing the textual content of AI-related patents (filed over the past 25 years) and linking them to ISCO-08 3-digit occupational descriptions using a pre-trained model for semantic similarity. We combine this measure with data from the Italian Labour Force Survey to quantify the employment shares of AI-exposed occupations across sectors classified by technological level and knowledge intensity. Furthermore, we analyze the geographical distribution of these occupations across Italy’s macro-regions to assess potential spatial inequalities in AI-driven labor market transformation. The analysis reveals significant heterogeneity in exposure to AI both across sectors and territorial divisions. Sectors with high technological intensity tend to concentrate a larger share of occupations exposed to AI, while southern regions are structurally less represented in such segments, potentially exacerbating pre-existing regional gaps. These findings underline the importance of proactive policy responses aimed at fostering skill adaptation, enhancing digital infrastructure, and supporting vulnerable territories. In the broader context of the transition toward a knowledge-based economy, understanding the occupational and territorial dimensions of AI exposure is essential to ensure inclusive and equitable development.
- Keywords:
- Regional disparities,
- Artificial Intelligence,
- AI Exposure Index,
- Labour Market Transformation,
ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0009-0003-5424-3227
ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0009-0004-7003-3243
ISTAT, Italian National Institute of Statistics, Italy
ISTAT, Italian National Institute of Statistics, Italy
ISTAT, Italian National Institute of Statistics, Italy - ORCID: 0009-0001-7980-7012
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Informazioni sul capitolo
Titolo del capitolo
The unequal geography of artificial intelligence: Labor market exposure and regional disparities in Italy
Autori
Massimo Armenise, Mauro Bruno, Luigi De Iaco, Marianna Mantuano, Giulio Massacci
Lingua
Inglese
DOI
10.36253/979-12-215-1062-1.8
Opera sottoposta a peer review
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
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
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