Artificial Intelligence into Italian Permitting 5.0 System

ID: 2069

Presenting Author: Gianluigi Nocco

Session: 541 - EsIA and Permitting Improvements for Efficiency and Effectiveness: Lessons Learned

Status: pending


Summary Statement

The project introduces artificial intelligence into Italy’s permitting system to enhance environmental impact assessment efficiency and transparency through the Permitting 5.0 model.


Abstract

Artificial Intelligence is profoundly transforming environmental impact assessment, creating new opportunities to structure knowledge, support decision-making, and streamline administrative processes. In this context, the Italian Ministry of the Environment and Energy Security (MASE) is leading the implementation of a national Permitting 5.0 model, integrating digital systems and AI tools across all levels of environmental permitting—EIA, SEA, IPPC, and DNSH.
The initiative establishes an institutional and scientific platform for co-designing and validating AI-supported methodologies for environmental evaluation. The project follows a five-phase roadmap: methodological sharing of the Permitting 5.0 model; activation of regional knowledge frameworks; inter-institutional validation and co-design; implementation of the integrated system at national, regional, and local scales; and experimental management and adaptive monitoring of system performance.
Through these stages, the project aims to build a harmonized digital ecosystem that allows authorities and proponents to access shared environmental data, perform automated analyses, and continuously improve mitigation and compensation measures. The Italian Permitting 5.0 approach, coordinated by MASE, represents a pioneering effort to align artificial intelligence with regulatory, technical, and participatory dimensions of environmental governance—positioning Italy as a European model for sustainable permitting innovation.


Author Bio

Gianluigi Nocco, Director General for Environmental Assessments at MASE, leads national strategies to enhance transparency, efficiency, and scientific rigor in environmental permitting and s


Coauthor 1: Annamaria Maggiore

Coauthor 2: Monica Torchio

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