This paper analyses the potential of Artificial Intelligence and deep learning to revitalise tourism in Italy’s inland areas, within the framework of the National Strategy (SNAI). Addressing challenges of depopulation and fragmentation, the study explores how predictive and immersive technologies can foster sustainable tourism (undertourism) by enhancing offer personalisation and local SMEs’ efficiency. The work proposes the Destination Digital Twin as a systemic governance infrastructure, capable of integrating heterogeneous data and overcoming isolated projects to ensure integrated and resilient territorial management.
Il contributo analizza il potenziale dell’Intelligenza Artificiale e del deep learning nel rilancio turistico delle Aree Interne italiane, contestualizzate nella Strategia Nazionale (SNAI). Di fronte alle sfide dello spopolamento e della frammentazione, si indaga in che modo le tecnologie predittive e immersive possano favorire un turismo sostenibile (undertourism), migliorando la personalizzazione dell’offerta e l’efficienza delle PMI locali. Lo studio culmina nella proposta del Destination Digital Twin come infrastruttura sistemica di governance, capace di integrare dati eterogenei e di superare la logica dei progetti isolati, per una gestione territoriale integrata e resiliente.
DEEP LEARNING, IA E PROMOZIONE DELLE AREE INTERNE
Giovanni Barretta
;Vincenzo Camuso
;Guido Tortorella Esposito
2026-01-01
Abstract
This paper analyses the potential of Artificial Intelligence and deep learning to revitalise tourism in Italy’s inland areas, within the framework of the National Strategy (SNAI). Addressing challenges of depopulation and fragmentation, the study explores how predictive and immersive technologies can foster sustainable tourism (undertourism) by enhancing offer personalisation and local SMEs’ efficiency. The work proposes the Destination Digital Twin as a systemic governance infrastructure, capable of integrating heterogeneous data and overcoming isolated projects to ensure integrated and resilient territorial management.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


