Italian Strategy for Artificial Intelligence 2024-2026
ITALIAN STRATEGY FOR ARTIFICIAL INTELLIGENCE 2024-2026
The Italian Strategy for Artificial Intelligence 2024-2026 sets out Italy's national plan to foster AI development and adoption while ensuring alignment with European values and regulations. Structured around four macro-areas—Research, Public Administration, Enterprises, and Training—the strategy aims to enhance national competitiveness, improve public services, support economic growth, and address skills gaps through coordinated investments and governance mechanisms. It emphasizes the creation of national knowledge assets, public-private partnerships, and robust monitoring to mitigate risks such as non-action, homogenization, and digital divide.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Policymakers, public administration officials, researchers, enterprises, and educational institutions looking to understand or participate in Italy's national AI roadmap.
What the document contains
The document covers strategic objectives and actions across four main areas: research, public administration, enterprise innovation and adoption, and training and education. It also outlines enabling infrastructures, coordination mechanisms via a new Foundation, risk assessments, monitoring frameworks, and the regulatory context including European AI Act alignment.
Specific binding legislation or direct statutory enactments, as it is a strategic policy document rather than primary legislation.
- The strategy provides a comprehensive framework to guide Italy's AI development and adoption across research, public administration, enterprises, and training for 2024-2026.
- It emphasizes the creation of anthropocentric, reliable, and sustainable AI solutions that respect European values and protect national interests.
- A dedicated Foundation for Artificial Intelligence is proposed to oversee implementation, coordination, funding, and strategy monitoring.
- The plan addresses critical gaps in digital skills and AI talent through extensive upskilling, reskilling, and integration into school and university curricula.
- It stresses the importance of avoiding the risk of non-action and cultural homogenization by developing domestic datasets, models, and robust public-private partnerships.
· 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.
Fairness
4/5Non-discrimination and equitable treatment
transparency of training data, to ensure compliance with non-discrimination laws, privacy (GDPR), human rights protection
R.3
screening score · 2026-10-23
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
A.1
screening score · 2026-10-23