Slovakia is preparing its own artificial intelligence strategy and is transposing the European AI Act into national legislation. Alongside regulation, attention is focused on education: the Ministry of Education is preparing an implementation plan to make AI a routine part of education without deepening the digital divide. The Czech model combining state data centers and cloud services also offers inspiration.
Regulation and responsible deployment in the public sector
According to the ministry responsible for informatization, a working group has been formed that is transposing the AI Act and preparing a law on artificial intelligence. The goal is to set clear rules for the use of AI in public administration, ensure data security, and prevent new tools from jeopardizing the functioning of the state. In addition to the law, implementing regulations and methodologies are to follow, which will make it easier for authorities to practically deploy models and services.
Experts note that a strategy by itself will neither start nor stop AI development—that is already underway. What is needed is sensible regulation, not unnecessary obstacles, and strategic decisions about infrastructure (for example, a hybrid or on-prem approach). The state should also invest in areas that the market will not develop on its own but that have long-term benefits for society.
Data, infrastructure, and Czech inspiration
The Czech Republic has chosen a "dual" model: critical and sensitive data remain in state data centers, and their own AI platform runs on them, while less sensitive data use cloud tools. The advantage is that data do not leave the government environment, and the central service provider can build specific AI solutions for ministries based on their data. Several countries in the region are considering a similar approach, and it also appears to be a realistic path in Slovakia.
The Slovak supercomputer Perún has, according to the ministry, sufficient performance for national AI projects and research, but experts warn that its capacity cannot be enough "for everything." It is therefore important to use HPC for training and experiments, diversify technologies, and keep pace with rapid developments (including trends such as quantum computing). Key decisions about data and infrastructure must go hand in hand with rules for security and privacy protection.
Education: four pillars of implementation
The Ministry of Education links strategy with implementation: the plan is to be ready in September and will cover the next two years. The first pillar is the introduction of AI into the curricula of primary and secondary schools so that systematic instruction begins as early as the next school year. The second is equal access—the state wants to broker useful AI tools for all students regardless of background and to build on investments in digital infrastructure (e.g., DigEdu). Partnerships are being sought with several major players; this is not about a subscription for a single tool, but about the availability of safe solutions in schools.
The third pillar is practical support within the sector: AI is to support curricular changes, students’ special needs, and relieve teachers of routine tasks (for example, in lesson planning). The fourth pillar targets research and university programs that are to prepare a new generation of specialists. The ministry is testing pilots with the OECD (an AI tutor for mathematics and a tool for translating curriculum into instruction) and does not want to dictate specific vendors to schools. Coordination with MIRRI is to ensure funding, rules, and competence centers; the goal is for AI to become a tool for better learning, less inequality, and graduates’ readiness for the labor market.
