Italian Strategy for Artificial Intelligence 2024-2026
ITALIAN STRATEGY FOR ARTIFICIAL INTELLIGENCE 2024-2026
The Italian Strategy for Artificial Intelligence 2024-2026 sets out a comprehensive national roadmap to foster AI research, public administration efficiency, enterprise innovation, and education. Issued by the Agency for Digital Italy, the strategy prioritizes anthropocentric, reliable, and sustainable AI solutions tailored to Italy's industrial and social context. It addresses key risks such as technological non-action, cultural homogenization, over-regulation, and the digital divide through targeted governance, data infrastructure, and funding mechanisms.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Policymakers, public administrators, business leaders, researchers, and educators seeking guidance on Italy's national vision and priorities for artificial intelligence.
What the document contains
The document addresses national policies, infrastructural requirements, funding mechanisms, research support, public administration efficiency improvements, enterprise adoption facilitators, and educational programs for artificial intelligence in Italy from 2024 to 2026.
The document does not establish binding primary legislation or direct statutory penalties, serving instead as a strategic planning framework.
- The strategy outlines four macro-areas for action: Research, Public Administration, Enterprises, and Training.
- It establishes a National Knowledge Assets registry to facilitate the sharing and reuse of trustworthy datasets and AI models.
- A dedicated Foundation for Artificial Intelligence will be created under the Presidency of the Council of Ministers to coordinate implementation and monitoring.
- The document emphasizes the need for Italian Large Molecule Models (LMM) to preserve national identity, values, and compliance with European regulations.
- Upskilling and reskilling programs are highlighted as crucial measures to bridge workforce gaps and prevent a digital knowledge divide.
· INTRODUCTION · CONTEXT ANALYSIS · PRINCIPLES OF THE STRATEGY · STRATEGY DESIGN · STRATEGY FOR RESEARCH · STRATEGY FOR PUBLIC ADMINISTRATION · STRATEGY FOR ENTERPRISES · STRATEGY FOR TRAINING · MONITORING THE STRATEGY · REGULATORY BODIES
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
3/5Clear responsibility for AI outcomes
research on new challenges created by AI on issues such as copyright, deepfakes, online disinformation, and responsibility; research on ethics and AI; studying the socio-economic impacts of AI
Strategy for Research - R.4 | SYNERGIES: INTERDISCIPLINARY PROJECTS FOR SOCIAL WELLBEING
screening score · 2026-10-24
Enforcement
4/5Consequences and compliance mechanisms with real force
All projects funded within the national strategy or otherwise receiving public funding will be required to report the datasets used and the models produced in the registry
Enabling Strategic Actions - A.1 | NATIONAL KNOWLEDGE ASSETS: DATASETS AND MODELS
screening score · 2026-10-24
Impact Assessment
3/5Required assessment of an AI system's risks/impacts before or during use
It will be the responsibility of the Public Administration to identify specific areas of intervention, defining the policies to be adopted and assessing the impact and possible risks of the systems.
Strategy for Public Administration - PA.5 | EFFICIENCY ENHANCEMENT OF PUBLIC ADMINISTRATION
screening score · 2026-10-24