While the United States remains a world leader in artificial intelligence development with tech giants such as NVIDIA, Google, and OpenAI engaged in a global AI race to develop cutting edge technologies, other nations are embracing AI as a powerful and transformative tool for education.
Across Europe, AI is changing how students learn and teachers work. Yet while many schools and educators are already using generative tools in their daily routines, governments are still deciding how to regulate, support, and monitor this groundbreaking technological shift.
The Index covers six countries: Spain, Italy, France, Austria, Germany, and the United Kingdom. It also includes three additional honourable mentions with regard to AI capacity building: the Netherlands, Estonia, and Poland have all demonstrated promising initiatives with regard to educational AI integration.
1. Key Takeaways
2. What is the EU AI Act?
3. How was the European Educational AI Index Developed?
4. How to Read the Index
5. European Leaders within Educational AI Integration
6. Spain
7. Italy
8. Countries at Mid-Stage of Educational AI Development
9. France
10. Austria
11. Emerging Countries within Educational AI Planning
12. Germany
13. The UK
14. Honourable Mentions
15. The Netherlands
16. Estonia
17. Poland
18. Becoming Global Leaders in Artificial Intelligence
Which countries already have national plans and monitoring systems?
Which countries are focusing on teacher capacity and ethical standards?
Where is AI being used on an informal basis in classrooms ahead of public policy implementation?
By tracking progress and readiness across Europe, the Index seeks to support policymakers, educators, and researchers in shaping an educational future where AI is used responsibly, ethically, and effectively. It draws on standards set by the EU AI Act to determine each country's current and projected AI readiness.
The Artificial Intelligence Act (AI Act) is a European regulation that provides a legal framework for the development, requirements, organisation and application of AI technology:
The assessment and regulation of risk within an environment of rapid growth, particularly with regard to AI autonomous systems and vunerable or marginalized demographics
Ethical considerations surrounding the development, application and uses of machine learning, natural language processing, AI platforms, facial recognition technology, computer vision, and other tools.
The provision of best practice guidance for AI research
The promotion of AI excellence in innovation, including support for AI startups
Tthe mitigation of potential ethical concerns regarding AI ecosystems and products developed by major corporations
The Index is grounded in a comparative framework developed through the analysis of official government strategies, ministerial guidelines, and education-specific AI plans published between 2023 and 2025.
It measures AI capabilities, AI innovation and AI ethics, among other important technological development factors within Europe's educational institutions
Each country was assessed on seven dimensions that reflect both strategic readiness and practical implementation:
|
Dimension |
What it Measures |
|
Strategic Vision and Goals |
The presence of a coherent national vision for AI in education, integrated with broader digital or innovation strategies |
|
Principles and Ethics |
How clearly ethical standards, data protection, human oversight, and inclusion are embedded in policy documents and teacher guidance |
|
Legal and Regulatory basis |
The existence of binding legal instruments or ministerial decrees that regulate AI use in education, aligned with the EU AI Act and GDPR law |
|
Implementation Model |
The extent to which plans have moved forward from discussion to structured, funded implementation (pilots, national platforms, timelines) |
|
Applications and Use Cases |
The degree of classroom-level integration: teacher tools, student learning applications, and administrative systems |
|
Governance and Monitoring |
Mechanisms for supervision, data collection, evaluation, and accountability |
|
Training and Capacity building |
National frameworks and initiatives for equipping teachers and school leaders with AI skills and pedagogical competencies |
Each of these dimensions are rated on a 1-to-5 scale:
|
Score |
Description |
|
⭐⭐⭐⭐⭐ |
Clear framework, nationwide application, monitoring mechanisms active |
|
⭐⭐⭐⭐ |
Official plan or framework adopted; rollout underway but not yet universal |
|
⭐⭐⭐ |
Concrete initiatives, pilots, or drafts exist, but full implementation is pending |
|
⭐⭐ |
Disconnected pilots, working groups, or regional initiatives without national coherence |
|
⭐ |
No strategy, guidelines, or structured discussion specific to AI in education |
A country's overall score represents its average maturity across all seven dimensions: a government might excel in ethical principles, but remain behind in teacher training or monitoring, for example.
The European Educational AI Index does not measure 'innovation enthusiasm', but policy maturity, which denotes how close each country is to ensuring that AI enhances learning safely, ethically, and sustainably.
This means that a high score reflects objective coherence as opposed to media hype. Likewise, a low score indicates fragmentation or a lack of formal governance, which may be the case even if individual schools within a country are already experimenting with AI.
As national education systems differ in governance models, funding structures, and administrative traditions, the Index does not compare plan formats, but instead assesses their stage of maturity. A country can therefore score highly whether it adopts a centralised framework (as in Italy) or a distributed innovation model (as in Germany), provided that implementation, monitoring, and training mechanisms are demonstrably in place.
Spain leads the rankings in AI for education, scoring a total of 4.6, with five points awarded for the dimensions of Principles and Ethics and Training and Capacity Building. It received three points for the dimensions of Governance and Monitoring and Implementation Model.
Italy is in second place with a total score of 3.8, with five points awarded for the dimensions Applications and Use Cases, and Governance and Monitoring. It is held back by a lower score of two points in the dimension of Principles and Ethics
France ranks third, scoring a total of 3.3, with five points awarded for the dimensions of Principles and Ethics, but only two points for the dimension of Governance and Monitoring
Austria comes in fourth place with a total score of 3, with four points awarded for the dimensions of Legal and Regulatory Basis and Training and Capacity, but receiving two points for Strategic Vision and Goals
Germany ranks fifth with its AI development plans scoring a total of 2.7, with four points awarded for the the dimensions of Principle and Ethics, and Training and Capacity Building, with one point for Governance and Monitoring
The UK scores a total of 2.4 for its emerging strategy, receiving three points for the dimension of Principles and Ethics, Implementation Model, and Governance and Monitoring, but with further development needed for other areas
Implementation Stage: 🟢Implementing
Spain has developed a comprehensive strategic plan for artificial intelligence use within its education systems. It recognises the value of incorporating AI technology in classrooms for students of all ages, establishing a pro-social approach to faculty training, together with an exceptional emphasis on ethics and safety.
Strategic Vision and Goals ⭐⭐⭐⭐
Promote responsible, safe, and ethical use of AI in education
Develop AI literacy among students and teachers
Prepare schools to adapt to technological change
AI education is part of Spain’s broader “Digital Spain 2026” strategy
Principles and Ethics ⭐⭐⭐⭐⭐
Strong focus on ethical challenges and security
Considers UNESCO’s ethical AI in education recommendations and EU frameworks (EU AI Act)
Emphasis on ethical AI literacy and issues related to AI use for both teachers and students
Legal and Regulatory Basis ⭐⭐⭐⭐
References the EU AI Act, GDPR, and Spain’s national data protection laws (LOPDGDD)
Recommends schools conduct Data Protection Impact Assessments (DPIA) for AI tools, and clarifies that responsibility lies with educational authorities to ensure compliance
No new AI-specific legislation for education as of yet, but clear legal integration is present
Implementation Model ⭐⭐⭐
The official guide acts as a national reference framework, not a prescriptive rollout plan
Guidance is provided for schools to evaluate and responsibly adopt AI tools. The document suggests the creation of local AI action plans at school or regional levels
Pilot initiatives, including “IA en el aula” projects are running with regional support in Catalonia and Andalusia
Applications and Use Cases ⭐⭐⭐⭐
Listed educational uses include personalised learning, formative assessment, administrative automation, accessibility for students with special needs, and teacher assistance
Warnings included regarding generative AI limits and the need for human validation
Governance and Monitoring⭐⭐⭐
The guide emphasises governance principles, stating that schools should form AI oversight committees, ensure continuous monitoring of risks, and evaluate impacts on teaching quality and equality
No central monitoring authority or KPI system defined as of yet
Training and Capacity Building ⭐⭐⭐⭐⭐
The Instituto Nacional de Tecnologías Educativas y de Formación del Profesorado (INTEF, National Institute of Educational Technology and Teacher Training) denotes a dedicated mission to teacher training within AI
The guide links AI competence to the Marco de Referencia de la Competencia Digital Docente (MRCDD, Digital Competence in Teaching Framework)
INTEF is producing training materials, MOOCs and webinars on AI in education, in addition to establishing professional learning communities
Implementation Stage: 🟢Implementing
Italy's vision for AI in schools aims to increase access to personalised learning while improving administrative and management efficacy. The country's plan has emphasised the importance of developing critical thinking skills among students as a complement to digital fluency.
Strategic Vision and Goals ⭐⭐⭐⭐
AI is seen as a transformative technology for education, administration and management
Main goals are: personalised learning, innovation in education, improved efficiency in administration, transparency, and the development of digital skills and critical thinking.
Initial projects will focus on validating the hypothesis that AI can add value to teaching and educational experiences
Principles and Ethics ⭐⭐
Principles focus on human-centeredness, equity, ethical innovation, transparency and non-discrimination
Ethical requirements emphasise inclusivity, explainability, and accountability (focus on ethical AI literacy is not currently present)
Legal and Regulatory Basis⭐⭐⭐⭐
GDPR and AI Act compliance guarantees privacy by design
Guidelines endoresed by the Italian Data Protection Authority (Garante)
Garante ensures students' data privacy for tests led by the National Institute for the Evaluation of Instruction and Training (INVALSI)
No specific law in place to regulate AI in schools
Implementation Model ⭐⭐⭐⭐
Provides a full life cycle framework of AI implementation in education from design to use
UNICA, a platform developed by the Ministry of Education and Merit (MIM) provides teachers and students with access to digital learning resources and tools
Students in their final three years secondary school will be the first to test new technology
Applications and Use Cases ⭐⭐⭐⭐⭐
School head teachers should be in charge of leading the AI initiative and implementation
Administrative staff, teachers and students shall benefit from using AI
The Ministry of Education is collaborating with Google to offer tools, such as Gemini, together with guided exercises, for teenaged students
Governance and Monitoring ⭐⭐⭐⭐⭐
UNICA will offer a map of initiatives to track the evolution of pilots, with INVALSI to review results
Training and Capacity Building ⭐⭐⭐
First experimental project will involve 15 classes in the regions of Lazio, Lombardia, Toscana and Calabria
Training will take place through UNICA, but will be self-lead without adherance to specific timelines or assessments
Implementation Stage: 🟡 Early Implementation
In June 2025, France's National Ministry of Education established the L’IA en éducation: Cadre d’usage (AI in Education: Usage Framework), outlining the goals of educational AI implementation along with its necessary restrictions. Strong compliance regulations apply to the key areas of data use and human oversight.
Strategic Vision and Goals ⭐⭐⭐
AI viewed as a transformative technology to be understood, used critically, and integrated responsibly in education.
Emphasis on using AI to strengthen civic and scientific literacy, and to support teachers.
Framework for use; not a national strategy with defined timelines or funding.
Formal plan set to be published in Spring 2026.
General AI plan does take educational AI into consideration.
Principles and Ethics⭐⭐⭐⭐⭐
Ethical considerations are at the heart of the cadre d’usage: respect for the values held by the French Republic, human oversight, frugal and environmentally conscious AI, inclusion, accessibility, equity, and preference for open-source tools.
Strong emphasis on critical thinking and transparency.
Legal and Regulatory Basis ⭐⭐⭐⭐
The framework is grounded in the Code de l’éducation, GDPR, Loi Informatique et Libertés, SREN, and the EU AI Act.
It outlines strict compliance for data use and human oversight in high-risk systems.
Implementation Model ⭐⭐⭐
A total of €20 million has been allocated to the creation of AI tools for teachers and students.
A specific tool for teachers has been announced, and is set to launch in 2026-2027.
Secondary school students undertake a 30-90 minute training session through the French NGO digital learning platform, Pix, to assess their level of AI knowledge, helping to close the access to AI gap.
Applications and Use Cases ⭐⭐⭐
First trainings and tests for secondary education students.
According to the Cadre d’usage, students in class level 4e and above will be permitted to use AI autonomously in the classroom.
Governance and Monitoring ⭐⭐
The framework requires transparency and supervision for any AI-assisted decision-making, however the French government has not established a national monitoring body or dashboard.
Accountability remains local (head teachers, inspection).
Training and Capacity Building ⭐⭐⭐
Between 30 - 90 minutes of mandatory AI training has been implemented this school year for secondary school students.
While not mandatory, training in AI will also be available for teachers and other secondary students
Teachers are not due to receive mandatory training as of yet.
Implementation Stage:🟡 Early Implementation
Austria has adopted a decentralised approach to AI in education, with individual pilot schemes and localised ethics guidelines for teachers. While government discussions of legal issues surrounding artificial intelligence in education have taken place, school-specific legislation has yet to be established.
Strategic Vision ⭐⭐
The federal plan, AIM AT 2030, has been established, however it does not contain specific guidelines for education.
Various initiatives have been piloted, but not centralised, resulting in a lack of clarity around the national AI in education mission.
Principles and Ethics ⭐⭐⭐
Critical reflection, transparency and data protection for schools.
Several teacher training institutions have published local ethical rules.
Legal and Regulatory Basis ⭐⭐⭐⭐
Austria follows EU law (AI Act) and national data protection rules; official documents and commentary state that any school use must comply with GDPR and national laws.
Several official government websites discuss AI Act implementation and legal issues for public administration and education.
While the approach is rooted in legal alignment and guidance, no single education-specific AI law exists as of yet.
Implementation Model⭐⭐⭐
Implementation is decentralised: the BMBWF offers handbooks, a good-practice collection, and pilot coordination, while regions, universities (e.g., pedagogical universities) and civil society run pilots and teacher training programmes, and provide access to AI tools.
Applications and Use Cases⭐⭐⭐
Pedagogical uses (personalised learning, assessment support, accessibility), administrative uses (workflow automation) and careful, localised piloting in some regions and schools.
First pilots for testing AI applications primarily focused on generative language models (with an emphasis on teachers’ use of AI).
Governance and Monitoring ⭐⭐
The Federal Ministry of Education has documented the outcomes of pilot schemes, as opposed to conducting empirical studies using test and comparison groups.
Teachers were accompanied by researchers during the pilot documentation process. The results serve to demonstrate the potential outcomes of implementing AI in educational settings.
Training and Capacity Building ⭐⭐⭐⭐
A clear emphasis on teacher training is present.
Teacher training led by pedagogical universities is underway for both in-service and pre-service professionals, including the production of AI use guidelines and CPD modules.
PH Tirol and NGO providers have provided courses and guidelines.
A limited number of AI resources, materials, and tools are available via the Eduthek platform.
Implementation Stage:🔴Emerging (Framework Stage)
Germany's commitment to transparency and human oversight are guiding the country's strategy development for integrating AI within its education systems. At present, future implementation is seet to remain the responsibility of Germany's federal states, as opposed to the national government.
Strategic Vision and Goals ⭐⭐⭐
The National AI strategy adopted in 2018 is now considered to be outdated.
The Standing Conference of the Ministers of Education and Cultural Affairs (KMK) established a set of national guidelines in 2024, which are currently being used to inform plans under development by Germany's federal states.
Principle goals are to equip schools, and provide teachers and students with training that allows them to understand and use AI critically while ensuring pedagogical benefit and human oversight.
Additional focus is placed on the use of AI to improve teaching quality and enhance digital maturity within schools.
Principles and Ethics ⭐⭐⭐⭐
Emphasis on transparency, accountability, fairness, data protection, and human responsibility in AI-supported learning.
Approach rejects replacing human judgment with automated systems, stressing a reflective and critical use of AI.
Promotes equity and the closing of digital divides.
Legal and Regulatory Basis ⭐⭐
Reaffirms compliance with GDPR, copyright, and AI Act.
Recommendation for each state to define clear procedures for data protection and ethical AI use in classrooms.
Mentions the need for state-level rules ensuring AI use remains lawful and explainable. No current binding regulations in place.
Implementation Model ⭐⭐⭐
Pilot projects and co-creation between school practice, educational sciences, and technology providers to build AI applications suited for education.
Model encourages states to develop evaluation procedures for and quality audits of AI tools used in schools (possibly through a cross-state review process).
So far only recommendations, although official not binding. Implementation is responsibility of Germany's federal states (Länder) not the central government.
Applications and Use Cases ⭐⭐
Mentions pedagogical uses (personalised learning, assessment support, feedback tools) and administrative uses.
Strong focus on didactic integration and ethical assessment of AI use cases.
No specific tools or platforms have been announced. A state-generated centralised tool that allows access to multiple LLMs has been outlined.
Governance and Monitoring ⭐
Subject to the AI Act and GDPR, but no official government plan.
Suggests cross-state coordination and evaluation mechanisms.
The need to institutionalise AI is recognised, but has yet to be addressed.
Training and Capacity Building ⭐⭐⭐⭐
Training training is an exceptionally strong component of 2024 KMK guidelines: calls present for the systematic inclusion of AI in teacher education for both pre-service and in-service professionals.
Focus on teachers learning technical, ethical, and pedagogical aspects of AI, in addition to critical reflection, bias awareness, and data uses.
The Maximizing Effective Teaching AI (META) capacity building partnership with Stanford University has been establisehd to carry out practical research on teachers' needs regarding AI training, together with their use of AI tools in professional settings.
Implementation Stage:🔴Emerging
The UK hosted the 2023 AI Safety Summit, which sought to address risks associated within emerging technology in AI operating environments. The country takes a positive view of AI use within educational settings, adopting a focus on the easing of faulty workloads, and the potential to raise learning standards through technology.
Strategic Vision and Goals ⭐⭐
To use AI with two purposes: to reduce teacher workloads and to improve educational quality through innovation.
A national AI-in-education strategy has yet to be defined; targeted guidance and pilot support are present, however.
Principles and Ethics ⭐⭐⭐
Ethical principles: AI must never undermine human oversight, safeguarding protocols, fairness, or data protection procedures.
Risk assessment, transparency, and supervision are emphasised with regard to students' use of AI tools, particularly for students under the age of 18.
Legal and Regulatory Basis ⭐⭐
Compliance with UK GDPR and IP/Copyright law. No AI-specific education legislation.
Implementation Model ⭐⭐⭐
Implementation is bottom-up and led on a voluntary basis.
Initial trial programmes focused on teacher’s support and capabilities.
Three million GBP invested in support materials and content stores, with a focus on machine learning and LLM training to meet the needs of teachers and pupils.
Personalisation of student learning is noted as a use case.
Applications and Use Cases ⭐⭐
Mostly teacher support with grading, creation of resources, personalisation, etc.
Lack of analysis regarding specific student demographics and their use of AI tools.
No analysis of how students are already engaging with AI technology, and the importance of educating them on it uses and risks.
Governance and Monitoring ⭐⭐⭐
Ofsted is researching AI’s impact on 'early adopter' schools.
The DfE publishes ongoing updates through the AI in Education Collection on GOV.UK, however, no formal monitoring or accountability system is in place as of yet - compliance depends on existing inspection and data-protection regimes.
Training and Capacity Building ⭐⭐
Oak National Academy (funded by the UK government) is creating new tools for teachers, including Aila, an AI-powered lesson planning assistant which is available to British educators.
No mandatory training programmes in place.
The following European countries are also contributing to the formation of the global AI landscape, carrying out unique research projects and pilot schemes that address key factors that determine the successful integration of AI within educational institutions:
Through NOLAI (National Education Lab AI), the Netherlands is pioneering a collaborative, human-centred approach to AI in education. Funded by the National Growth Fund and coordinated by Radboud University, NOLAI unites schools, researchers, EdTech companies, and policymakers to co-create AI tools that are ethical, transparent, and pedagogically sound.
NOLAI operates under strict EU and national data and ethics frameworks (including the GDPR and EU AI Act), and has an integrated Ethics Board. Active since 2022, the initative runs classroom pilots across all education levels, focusing on adaptive learning, automated feedback, and teacher support systems. While strong governance, open collaboration, and teacher involvement define NOLAI’s model, broader policy adoption beyond the programme presents a future challenge.
Building on the success of its Tiger Leap digital education initiative, Estonia’s AI Leap strategy aims to make the country the “smartest nation through AI.” The plan focuses on maintaining high educational quality, personalising learning, and integrating innovative tools across schools.
With strong government and private backing (around 6.5 million euros annually), the initiative aims to upskill 58,000 students and 5,000 teachers by 2027 through free AI-based learning apps and teacher training. However, while Estonia leads in technological integration and innovation, its plan places less emphasis on AI literacy, data ethics, and mitigating potential risks associated with AI use in education.
Poland’s AI Development Policy 2025–2030 integrates AI into education through curriculum reform, infrastructure investment, and teacher training. Approximately 1.84 billion PLN will fund 16,000 AI-equipped classrooms, together with pilot AI labs and the “Generation AI” project in Katowice.
National coordination signals strong governmental involvement and growing readiness to deploy AI responsibly across schools, with teacher capacity building and public–private partnerships (e.g., Microsoft, Orange Foundation) supporting skills development.
Oversight mechanisms and evaluation frameworks are still evolving, however, and while ethical use and digital inclusion are emphasised, implementation details remain limited.
The AI revolution is set to transform the shape of education on a global scale, providing fertile ground for knowledge growth, talent development, and future innovation.
Societies worldwide are embracing technological advancements, investing heavily in data science and research and development, and constructing comprehensive, ethicial AI action plans. The impact on education is set to be profound and far-reaching, with many European countries primed to take their spot on the global stage in artificial intelligence development along with the USA, Canada and China.
Predicted economic growth within the global AI sector is estimated to reach 15.7 trillion USD by 2030, driving the need for AI-literate graduates and professionals
Significant investments are being made across European education systems to ensure students' fluency in AI systems
The ethical implemention of AI talent and innovation depends on legally binding regulations to guide and protect users, and to hold developers of the technology accountable.
As today's students step into a world being shaped by unprecedented technological evolution, AI action plans are critical in ensuring safe, stable environments in which they can learn, work, and live, both now and in the future.
For an indepth analysis of the impact of AI on European education, see the GoStudent Future of Education 2025 Report.