Tracking Europe’s progress on AI: Insights from the implementation of the EU Coordinated Plan on Artificial Intelligence

Since its launch in 2018, the European Union’s Coordinated Plan on Artificial Intelligence has represented a shared vision between the European Commission and EU Member States to develop, deploy and use artificial intelligence (AI) responsibly and strategically across Europe. Revised in 2021, the plan aims to mobilise at least EUR 20 billion in combined annual investments by 2030, strengthen Europe’s global position in trustworthy AI, and ensure that AI contributes to sustainable, inclusive growth.

A new OECD report, in cooperation with and funded by the European Commission, Progress in Implementing the European Union Coordinated Plan on Artificial Intelligence (Volume 1): Member States’ Actions, takes stock of national strategies, investments and governance arrangements shaping AI policy across the EU. Drawing on survey responses and interviews with national authorities across the EU Member States, it offers a comprehensive overview of policy initiatives in key areas, including AI policy, data, compute, skills, and support for AI adoption and innovative AI ventures.

A coordinated yet diverse approach

Nearly all EU Member States—24 out of 27—have now adopted national AI strategies, with the remaining three in the process of doing so. These strategies are informed by the EU Coordinated Plan and also address specific national priorities. Many have recently been updated or are being revised to respond to regulatory developments, rapid advances in generative AI, and evolving policy objectives. This dynamism demonstrates Europe’s adaptability but also highlights persistent differences in scope, funding and implementation.

Fewer than half of Member States have dedicated budgets for AI strategies. In most cases, AI is funded through broader digitalisation programmes or sector-specific initiatives led by different ministries. The lack of consistent budget tagging makes it difficult to isolate AI-specific expenditure and to monitor collective progress toward the EUR 20 billion annual investment target.

Governance structures also vary widely. Some countries have created dedicated AI agencies or inter-ministerial co-ordination bodies, while others rely on central ministries such as those for the economy, innovation or digital affairs. A growing number of governments are establishing mechanisms to evaluate or update their AI strategies, although only a minority publish evaluation results or track progress against measurable indicators. The report suggests that EU-level benchmarks and common indicators could help improve transparency and comparability and contribute to evidence-based decision-making.

Watch the replay of the report launch

Building the foundations: Data, compute and infrastructure

AI’s effectiveness depends heavily on data quality and availability, as well as computing capacity. Fifteen Member States have adopted national data strategies, thereby recognising data as both a public good and an economic asset. Many promote open data policies, secure data-sharing frameworks, and interoperability standards to support AI development.

Meanwhile, the demand for secure, high-performance digital infrastructure is growing fast. Over two-thirds of Member States are strengthening high-performance computing (HPC) capabilities, often through the EuroHPC Joint Undertaking, and investing in edge computing, sovereign cloud models, and connectivity networks to support AI workloads. More than half support semiconductor R&D and manufacturing, in line with the objectives of the European Chips Act. Collectively, these initiatives aim to ensure Europe’s sovereignty and global competitiveness in AI.

From the lab to the market: Strengthening Europe’s AI ecosystem

A central pillar of the Coordinated Plan is making Europe “the right place for AI excellence.” Member States are scaling up support for AI research and innovation, often through large-scale national programmes and AI centres of excellence. More than half have established national or regional AI centres that serve as hubs for research, talent development, and industry collaboration. Yet cross-border co-operation remains limited—an area where stronger networking could amplify Europe’s collective impact.

At the same time, many countries are seeking to bridge the gap between research and market application. About two-thirds of Member States have launched initiatives to help firms—especially small and medium-sized enterprises (SMEs)—adopt AI. Throughout the EU, European Digital Innovation Hubs (EDIHs) provide SMEs with access to testbeds, expertise and financial support. Countries are also investing in testing and experimentation facilities to help businesses design, validate and scale AI solutions while navigating regulatory requirements.

Support for AI start-ups and scale-ups is also expanding, often as part of broader innovation frameworks. Several Member States have introduced venture capital schemes, deep-tech funds and incubators dedicated to AI, signalling growing recognition that access to finance and entrepreneurship support are key to sustaining Europe’s AI competitiveness.

Ensuring AI works for people

Consistent with the EU’s human-centric vision, Member States are increasingly embedding AI within education and skills strategies. More than half have introduced digital literacy programmes that include AI elements such as coding and algorithmic thinking. At the tertiary level, AI-focused degree programmes and doctoral initiatives are expanding, and some countries are integrating AI into disciplines beyond computer science—such as business, humanities and public administration.

Nevertheless, skills gaps remain. Most initiatives to attract AI talent focus on academia rather than on industry or the public sector. Similarly, while several Member States have launched AI-specific graduate and doctoral programmes, as well as upskilling and reskilling schemes, few systematically monitor participation or outcomes. Promoting gender inclusion in AI remains another challenge: many countries encourage women’s participation in STEM, but few have AI-specific gender initiatives.

Sectoral priorities: Where AI can have the biggest impact

Member States’ sectoral priorities are generally aligned with those identified in the EU Coordinated Plan—healthcare, public administration, mobility, climate and environment, and agriculture—but their intensity and focus vary across national contexts.

• Healthcare is among the domains attracting the most policy attention, promising improvements in diagnostics, patient experiences, and operational efficiency. Yet progress remains uneven due to fragmented data policies and limited cross-border co-ordination. Initiatives like the European Health Data Space (EHDS) could unlock significant potential by enabling secure, interoperable data sharing across countries.
• Environmental applications of AI are gaining ground, with more than two-thirds of Member States reporting initiatives leveraging AI to address climate and environmental challenges. Areas covered by these initiatives include energy efficiency, waste management, and resource optimisation. However, only a few address AI’s own environmental footprint, underscoring the need for more attention to sustainable computing and energy-efficient model design.
• In the public sector, 16 Member States have launched AI initiatives focusing on workflow automation, tax administration, citizen services and, to a lesser extent, supporting regulatory compliance or policymaking processes. While innovation hubs and regulatory sandboxes support experimentation, the report finds that skills and capacity building in the public workforce remain limited.
• Mobility is another fast-moving sector: 17 Member States have launched AI initiatives in transport, including automated and connected mobility systems. Yet, structured frameworks for data sharing and interoperability are rare, limiting the ability to scale these solutions across borders.
• In agriculture, two-thirds of Member States have introduced AI-related initiatives, often through testbeds, innovation hubs and support for agri-tech start-ups. However, data-sharing mechanisms and AI integration into rural development strategies, as well as application in forestry or the bioeconomy, remain limited, leaving significant untapped potential.

More coherence, shared indicators and coordination to face challenges ahead

Across these domains, Europe’s progress in implementing the Coordinated Plan reflects a genuine commitment to fostering responsible AI. Yet, the findings suggest that greater policy coherence, shared monitoring indicators, and enhanced cross-border co-ordination could help accelerate Europe’s journey toward trustworthy, human-centric AI. Strengthening data governance, investing in compute capacity, and promoting a well-skilled, diverse AI workforce will also be essential.

Ultimately, the EU Coordinated Plan on AI illustrates the value of collaboration in an era where AI’s opportunities and risks transcend borders. To further strengthen this collaboration, the European Commission has published its Apply AI Strategy and AI Continent Action Plan. Together with the European AI Office’s leadership, ambitious steps taken by EU Member States, and evidence and analysis provided by organisations such as the OECD, these initiatives constitute a clear common roadmap. They are, however, not endpoints but a framework for continuous learning and adjustment. It is now our collective responsibility to actively use that framework. To learn from each other, to invest where it matters most, and to ensure that AI in Europe is both innovative and trustworthy.