Progress Report on the Implementation of the EU Coordinated Plan on Artificial Intelligence (Volume 1): Actions by Member States

List of Key Chapter Titles

1. Overview
2. Creating the Conditions for AI Development and Uptake in the EU
3. Making the EU the Right Place: Excellence from the Lab to the Market
4. Ensuring AI Serves People
5. Building Strategic Leadership in High-Impact Areas
6. Acquiring, Pooling, and Sharing Policy Insights
7. Unlocking Data Potential and Nurturing Critical Computing Capacity
8. Building and Mobilizing Research Capacity
9. Funding and Promoting Innovative AI Ideas and Solutions
10. Nurturing Talent and Improving Skills Supply for a Thriving AI Ecosystem

Document Introduction

This report is the core output of the collaborative project "Monitoring the Implementation of the EU Coordinated Plan on AI" between the Organisation for Economic Co-operation and Development (OECD) and the European Commission. As the first volume in a series, this report focuses on policy implementation and action progress at the level of the 27 EU Member States. It systematically reviews the national strategies, governance frameworks, and specific measures adopted by each country since the 2021 revision of the EU Coordinated Plan on AI to support AI development and application. The report aims to comprehensively assess the current situation, identify common issues, showcase best practices, and provide an evidence-based foundation for promoting coordination and cooperation at the EU level.

The report's methodology combines desk research, targeted online surveys, and online interviews with relevant authorities in the Member States. The survey was conducted from July to October 2024, and the interviews took place from September to December 2024. Based on information collected and validated up to December 2024, the report compiled country notes. These were reviewed at meetings of the AI Governance Working Group (AIGO) and the AI Innovation Subgroup of the EU AI Board in June 2025, and feedback from participants was integrated.

The study finds that EU Member States have reached a broad consensus on AI strategy development. By the end of 2024, 24 Member States had adopted national AI strategies, with the remaining three in the process of developing them. The vast majority of these strategies are guided by the EU Coordinated Plan and have generally been updated or revised in recent years in response to the rise of generative AI, technological developments, and regulatory changes (such as the EU AI Act). However, significant differences exist among Member States regarding governance and monitoring. While most countries have established cross-ministerial coordination and multi-stakeholder governance structures, less than half have set clear Key Performance Indicators (KPIs) for their AI strategies, and regular public evaluation reports are not common practice. Tracking public investment in AI also faces challenges. Only a few countries have dedicated budgets for their AI strategies; most embed AI funding within broader digitalization strategies, making precise accounting and cross-country comparisons difficult.

Regarding the development of enabling conditions, over half of the Member States have a national data strategy, two-thirds have a cloud computing strategy, over two-thirds are strengthening high-performance computing capacity, and more than half support the development of the semiconductor ecosystem. Building research capacity is a pillar of most national strategies. Over half of the Member States have established national-level AI excellence centers and launched large-scale AI R&D funding programs. However, cross-center and cross-country collaboration networks remain weak. In promoting technology transfer and market uptake, European Digital Innovation Hubs are present in all Member States, providing technical support to businesses, especially SMEs. Nearly half of the Member States reported initiatives related to AI testing and experimentation facilities. Approximately two-thirds have introduced measures to help SMEs adopt AI and to support AI startups and scale-ups.

The report pays special attention to the implementation of the two pillars: "Human-centric AI" and "High-Impact Areas." In education and skills, Member States are integrating AI into digital literacy programs from primary to higher education and expanding adult reskilling initiatives. However, systematic monitoring of AI-related courses and graduate numbers is not yet widespread. Initiatives to attract AI talent also primarily focus on academia, with a noticeable lack of programs targeting industry needs. Regarding application in key sectors, healthcare and the public sector are the most commonly addressed areas in national AI strategies, followed by transport, climate and environment, and agriculture. Although application cases are increasing, Member States commonly face shared challenges such as policy fragmentation, limited cross-border coordination, inadequate data-sharing frameworks, and talent capital constraints, which limit AI's potential to fully realize its transformative power in these areas.