The European Union Coordinated Plan on Artificial Intelligence is a strategic initiative developed by the European Commission and EU Member States to promote development, deployment and use of AI technologies across the European Union. This chapter introduces the four pillars of the plan, as well as the methodology and objectives of this report. It also provides an overview of the key findings across the four thematic areas: actions undertaken by EU Member States to create the enabling conditions necessary for timely and effective AI development and uptake in the European Union; their efforts to strengthen and mobilise AI research capacities, to facilitate AI innovation and commercialisation, and support the adoption of AI-based solutions by EU firms; their initiatives to nurture talent and enhance the availability of AI-related skills within AI ecosystems; and their measures to build strategic leadership in high-impact sectors.
Progress in Implementing the European Union Coordinated Plan on Artificial Intelligence (Volume 1)
Abstract
This report is the main deliverable of Work Package 1 of Monitoring Progress in Implementing the European Union Coordinated Plan on Artificial Intelligence (hereafter “EU Coordinated Plan on AI”), which is a collaboration between the Organisation for Economic Co‑operation and Development (OECD) and the European Commission. Its main objective is to take stock of implementation of the national strategies and policy initiatives established by European Union (EU) Member States to support the development and uptake of artificial intelligence (AI), in line with the actions presented in the EU Coordinated Plan on AI, which was launched in 2018 and reviewed in 2021 (EC, 2018[1]).
The EU Coordinated Plan on AI is a strategic initiative to promote development, deployment and use of AI technologies across the European Union. It represents a joint commitment between the European Commission and EU Member States to maximise the impact of investments in AI, foster synergies and encourage co‑operation across the European Union. The plan outlines a series of concrete actions to facilitate investment decisions, aligning AI policy in the European Union to remove fragmentation. It also aims to contribute to strengthening the global position of the European Union regarding the development and adoption of human‑centric, sustainable, secure, inclusive and trustworthy AI technologies and applications.
The plan is organised around four key pillars (Figure 1.1), each addressing crucial aspects of AI development and implementation across the European Union. A key target in the plan relates to increasing the combined annual investment in AI by EU public and private sectors to at least EUR 20 billion by 2030. At the EU level, the Digital Europe Programme, Horizon Europe, and the Recovery and Resilience Facility provide funding opportunities to build strategic digital capacities, foster AI research and innovation, and support Member State investments and reforms.
The first pillar focuses on creating the enabling conditions necessary for AI development and adoption across the European Union. It emphasises the importance of building a robust ecosystem that fosters AI innovation and deployment. A key area of action within this pillar involves establishing effective governance and co‑ordination frameworks to facilitate the acquisition, accumulation and sharing of policy insights on AI. The pillar further includes initiatives to improve the availability, sharing and access to high-quality data – essential for training AI systems – as well as efforts to enhance critical computing infrastructure to support advanced AI applications. These efforts also comprise strategic investments in semiconductors to ensure the technological foundation needed for cutting-edge AI development.
The second pillar aims to make the European Union the right place for AI excellence – from laboratory research to market applications. This involves substantial support for research and innovation in AI technologies, including funding mechanisms for promising ideas and solutions. The pillar also emphasises the importance of scaling up AI innovations, particularly supporting start-ups and small and medium-sized enterprises in bringing their AI solutions to market. Furthermore, it includes plans to establish world‑reference testing facilities, enabling rigorous evaluation and refinement of AI technologies before widespread deployment.
The third pillar is centred around ensuring that AI works for people and is a force for good in society. This human-centric approach underscores the commitment of the European Union to developing AI that aligns with EU values and ethical standards. The pillar encompasses initiatives to nurture AI talent and improve relevant skills across the workforce, preparing EU citizens for an AI-driven future. It also involves developing an AI regulatory framework to ensure trust and accountability in AI systems, while promoting the EU human-centric approach to AI on the global stage. A notable achievement under this pillar is the adoption of the EU AI Act in June 2024 (Regulation (EU) 2024/1689).
The fourth pillar concentrates on building strategic leadership in high-impact sectors. Recognising the transformative potential of AI across various industries, this pillar targets the application of AI in critical sectors, namely climate and environment, healthcare, robotics, public sector, law enforcement, mobility and agriculture. By focusing on these key areas, the European Union aims to leverage AI to address pressing societal challenges while also strengthening its competitive position in strategically important domains.
Implementing the EU Coordinated Plan on AI is a joint responsibility of the European Commission and EU Member States. This report discusses actions to be implemented by EU Member States, with a primary focus on initiatives adopted since 2021 (i.e. the year in which the EU Coordinated Plan on AI was reviewed). However, certain foundational initiatives adopted earlier are mentioned for ease of reference. Two separate reports present findings related to the AI investment target (Fonteneau et al., 2025[2]) and AI uptake in four sectors (agriculture, healthcare, manufacturing, and mobility) (OECD, Forthcoming[3]).
The OECD developed the methodology in close co‑ordination with the European Commission to provide a comprehensive account of implementation progress of EU Member States. The methodology also aims at identifying and showcasing relevant initiatives that may be replicated more broadly. It combined i) desk research; ii) a targeted online survey; and iii) group online interviews with relevant authorities in EU Member States. These elements are briefly outlined in Table 1.1.
The survey took place between July and October 2024, with interviews held between September and December 2024. Based on these consultations, country notes were compiled for each EU Member State1 and validated with the respective authorities. All EU Member States responded to the survey and a large majority (23 of 27) participated in interviews. However, the level and depth of information provided varied significantly across countries. Where possible, gaps in information were supplemented through desk research.
The main report draws from information collected and validated up to December 2024, which serves as the cut-off date. The report and country notes were presented at the meetings of the Working Party on Artificial Intelligence Governance (AIGO) and of the EU AI Board’s Artificial Intelligence innovation sub-group meeting of June 2025 and considers delegate feedback received. Targeted updates referring to developments in 2025 were incorporated based on this input.
The following sections discuss the key findings by each thematic area, with a summary provided in Table 1.2.
Set enabling conditions for AI development and uptake in the EU
Nearly all EU Member States have adopted national AI strategies
As of December 2024, 24 of the 27 EU Member States had adopted national AI strategies, with the remaining three in the process of developing such strategies. Implementation progress varies considerably. Since the revision of the EU Coordinated Plan on AI in 2021, most national AI strategies have been updated or are being reviewed to align more closely with emerging technological trends, regulatory developments and national priorities. In particular, the rise of generative AI has elevated AI on national policy agendas. Recent updates in 2023 and 2024 focus on expanding AI infrastructure, fostering public-private collaboration and addressing the opportunities and risks presented by generative AI. Moreover, as foundational research capabilities and policy frameworks mature, EU Member States are increasingly focusing on promoting uptake.
Only 12 of 27 EU Member States have dedicated AI strategy budgets with specific financial allocations. The remainder finance AI through specific initiatives led by relevant ministries or rely on AI funding integrated into broader digitalisation strategies. All EU Member States reported multiple initiatives aligned with each thematic area of the EU Coordinated Plan on AI, financed through national budgets or EU-level programmes.
Most EU Member States considered the EU Coordinated Plan on AI in their national strategies, and several pointed to the Digital Decade programme (EC, 2025[4]), including its targets, as a useful reference. Although they widely regarded overarching goals of the EU Coordinated Plan on AI as valuable, national authorities expressed the need for more detailed, practical guidance on how to achieve these objectives. In practice, the content of national AI policies remains largely driven by domestic agendas, with limited evidence of structured cross-border or regional collaboration. Notable exceptions include areas of strategic EU interest that have been important enablers of cross-border co-operation. These include cloud computing, high-performance computing (HPC) and health-related initiatives like the 1+Million Genomes and Genomic Data Infrastructure projects.
Oversight of national AI policies is being strengthened
Governance structures for AI policy vary across EU Member States but generally combine centralised leadership, inter-ministerial co‑ordination and multi-stakeholder engagement. National AI strategies are typically led by ministries responsible for digitalisation, innovation, economy or research, with several countries also placing certain responsibilities at the Centre of Government. Moreover, some countries have introduced dedicated bodies to oversee AI compliance and governance, while stakeholder engagement in the formulation and revision of national AI strategies is a growing priority. Monitoring and evaluation practices of AI policies vary significantly across EU Member States in both approach and level of ambition. Co-ordination challenges have been reported in cases where monitoring responsibilities are scattered across various ministries in charge of specific projects or initiatives. Although more than half of EU Member States reported having evaluated their national AI strategies, relatively few of them have made evaluation results publicly available.
National-level efforts to unlock the value of data and strengthen compute capacity are gaining momentum
Fifteen EU Member States have adopted dedicated national data strategies, thereby acknowledging data as both a public good and a strategic economic asset. Open data initiatives represent a key area of focus across several EU countries, with varying approaches to increase transparency, accountability and data re-use. A growing number of countries are developing shared data environments to enable secure and standardised data exchange across sectors.
Strengthening compute capacity has become a key priority in EU Member States’ AI policies. EU Member States are increasingly investing in high-performance computing (HPC), edge computing, secure cloud environments, and connectivity networks to support the growing demand for AI workloads and decentralised data processing. These efforts align with EU-level frameworks such as Gaia-X, a European initiative aimed at developing a common data infrastructure, EuroHPC Joint Undertaking (JU), the Important project of Common European Interest (IPCEI) on Next-Generation Cloud Infrastructure, and the European Chips Act.
Make the EU the right place: excellence from lab to market
EU Member States are scaling up investments in AI research and development
Many national AI strategies prioritise long-term research and development (R&D) investment, with funding increasingly channelled through flagship programmes, research centres, and thematic calls aligned with societal and industrial goals. More than half of EU Member States have established national or regional AI centres of excellence that typically host cutting-edge R&D, support high-level talent development, and enable collaboration with industry. Many are further institutionalising R&D governance, e.g. through national R&D strategies, oversight councils, and formalised monitoring.
Several EU Member States reported investments in large language models and linguistic data resources. Moreover, the rise of generative AI has triggered a reassessment of research priorities and infrastructure needs while sparking new R&D challenges to which several EU Member States are responding by funding responsible AI frameworks in tandem with generative AI advances.
EU Member States support adoption of AI solutions by firms and commercialisation of AI innovations
AI, together with other digital technologies, can contribute significantly to the competitiveness of the EU economy by enhancing productivity and value creation. A key EU Digital Decade target consists of reaching 75% of businesses using digital technologies, including cloud, data analytics and AI, by 2030. Despite recent progress, AI adoption by EU firms remains however relatively modest and uneven.
About two-thirds of EU Member States have launched initiatives to promote AI uptake by firms, particularly SMEs. Although those initiatives are often part of broader digitalisation support efforts, several AI-specific programmes have been introduced to provide dedicated guidance and funding. In addition, platforms are being set up to facilitate collaboration between SMEs and AI solution providers, thereby addressing skills and expertise gaps and fostering knowledge transfer. European Digital Innovation Hubs (EDIHs) provide AI guidance, training, and SME support.
Around two-thirds of EU Member States reported initiatives aimed at helping AI start-ups and scale-ups access funding, which is crucial for accelerating deployment of advanced AI solutions and remain competitive internationally. Reported initiatives generally belong to broader innovation or entrepreneurship programmes. Support measures aimed at AI or deep tech ventures through venture capital (VC), incubators or accelerators are however gradually expanding.
Ensure AI technologies work for people
EU Member States are embedding AI into digital literacy programmes and expanding university-level AI education
EU Member States are introducing a growing number of measures to equip students with foundational digital and AI-related skills. More than half have launched digital literacy programmes for primary and secondary education often including AI components such as coding, robotics, or algorithmic thinking. AI-specific teacher training and university-level AI education are also gaining momentum, with growing efforts to integrate AI into fields such as humanities, business and governance. Initiatives to attract AI talent tend to focus on academia (researchers and doctoral candidates) rather than on attracting private sector professionals.
Many EU Member States are integrating AI into broader adult learning and digital skills strategies. At least 14 countries have adopted national strategies that include AI literacy as a key pillar. In addition, 12 have reported structured AI-specific upskilling schemes. Despite noteworthy efforts in these areas, relatively few EU Member States engage in systematic national-level monitoring of AI courses and graduate numbers.
Many EU Member States are promoting gender inclusion in STEM fields, laying important groundwork for more diverse participation in AI. However, examples of targeted efforts to promote gender inclusion in AI specifically remain scarce.
Build leadership in high-impact sectors
Sectoral priorities in national AI strategies are consistent with the EU Coordinated Plan on AI, but they also reflect national contexts
Sectoral priorities in national AI strategies are generally consistent with the EU Coordinated Plan. Strong focus is placed on healthcare, the public sector and mobility. Several countries are also aiming to leverage AI to support energy efficiency and the green transition. Education and skills are emerging areas of focus, with countries integrating AI into learning systems and workforce development. Agriculture, in turn, features primarily in the strategies of countries with strong farming sectors.
Despite growing efforts to foster AI use in these areas, EU Member States face common challenges, including fragmented policies, limited cross-border co‑ordination, human capital constraints, and underdeveloped data-sharing frameworks.
In healthcare, AI is emerging as a transformative tool that the Coordinated Plan encourages EU Member States to capitalise upon by contributing to better, interoperable data, working with medical professionals to increase understanding of potential benefits (better diagnostics, enhanced patient experience, more efficient management and operations, higher R&D productivity…) and address skills requirements, co-operate towards common standards, and support investment in several key projects and focus areas. This transformative potential remains however underutilised due to fragmented policies across borders, varying interpretation and application of EU legislation, and limited co‑ordination between national initiatives. Enhanced collaboration – e.g. through the implementation of the European Health Data Space (EHDS) – could help create a more resilient, safe and innovative AI health sector that builds on EU Member States’ individual strengths while reinforcing the Union’s position in the global health landscape.
Most EU Member States have taken steps to advance AI-based solutions that contribute to environment and climate policy goals. Fifteen EU Member States have introduced initiatives using AI to address sustainability challenges, ranging from energy efficiency and resource optimisation to waste management and disaster resilience. Comparatively fewer are however acting to improve environmental data infrastructures or mitigate AI’s resource intensity: seven EU Member States reported measures addressing AI’s environmental footprint, e.g. by improving the energy efficiency of AI models and data centres and promoting frugal AI research.
Sixteen EU Member States identified AI adoption in the public sector as a priority in their national AI strategies. Efforts in this area focus on workflow automation, citizen services, tax administration and regulatory compliance – with a total of 91 initiatives reported across 24 EU Member States. Some of these initiatives focus on specific topics, such as generative AI use, or levels of government, such as municipalities. Governance frameworks, ethical guidelines and transparency mechanisms also remain important priorities, while innovation hubs and regulatory sandboxes are being developed to support safe experimentation and deployment of AI solutions, and some countries are establishing incubators for public sector AI solutions. Enhanced efforts to build AI-related skills and capacity in the public workforce, including more investment in training and talent development, are nevertheless required. In addition, EU Member States continue to grapple with data fragmentation and infrastructure gaps that limit effective integration. Interoperability remains another significant challenge, particularly for federated AI systems and cross-border services.
Seventeen out of the 27 EU Member States reported specific initiatives to advance AI in mobility (49 in total). AI is increasingly embedded in broader strategies for sustainable mobility transformation, with eight countries reporting to have integrated AI into strategies or programmes for sustainable and resilient mobility system to help attain objectives ranging from traffic optimisation and multimodal integration to digital infrastructure upgrades. Coverage is however uneven. Automated mobility, for instance, has received substantial attention (with 11 countries reporting targeted initiatives including regulatory adaptations, testing infrastructure, and safety frameworks). In contrast, areas such as data sharing are seldom a core component of policy initiatives, e.g. only three EU Member States reported dedicated initiatives for mobility data sharing. Structured policies and strengthening interoperability and open data protocols could therefore unlock further benefits, enabling more seamless AI integration across national and cross-border mobility networks.
Two-thirds of EU Member States have launched initiatives to foster adoption of AI in agriculture, although the distribution of these efforts remains uneven across countries due to factors such as geography, barriers to adoption, farm type and size, agriculture’s relative economic weight, and digital literacy levels. The focus on agriculture varies depending on the sector’s economic importance within each country. Countries where agriculture plays a central role in the economy are more likely to prioritise AI integration in farming practices. AI is being leveraged in the sector to boost productivity, efficiency, and resilience through initiatives like testbeds, innovation hubs and support for agri-tech start-ups. Efforts are also underway to facilitate knowledge transfer and improve access to AI tools among farmers, particularly through the EDIH network. However, data-sharing initiatives remain limited. Few EU Member States reported either having integrated AI components into their rural development strategies or adopted initiatives focused on AI applications in forestry. This situation indicates untapped potential for developing comprehensive approaches to AI integration that extend beyond farm level applications as well as across the complete agricultural and environmental management spectrum.
References
[4] EC (2025), “Europe’s digital decade”, European Commission, https://digital-strategy.ec.europa.eu/en/policies/europes-digital-decade (accessed on 2024 August 2025).
[1] EC (2018), “Coordinated plan on artificial intelligence”, https://digital-strategy.ec.europa.eu/en/policies/plan-ai (accessed on 25 August 2024).
[2] Fonteneau, F. et al. (2025), “Advancing the measurement of investments in artificial intelligence”, OECD Artificial Intelligence Papers, No. 47, OECD Publishing, Paris, https://doi.org/10.1787/13e0da2f-en.
[3] OECD (Forthcoming), Progress in Implementing the European Union Coordinated Plan on Artificial Intelligence (Volume 2): AI uptake in high-impact sectors.
← 1. Due to insufficient information in the survey response, a full country note could not be compiled for Estonia.