The Complete Guide to Using AI in the Education Industry in Czech Republic in 2025

The Czech Republic's updated National AI Strategy 2030 makes AI education a national priority - listing “AI education and expertise” and lifelong learning among seven strategic pillars and calling for curriculum changes, teacher training and wider computational thinking across schools (see the Ministry's NAIS 2030 overview).

That national push is paired with fast-moving, practical initiatives: Microsoft's AI National Skilling Plan aims to train 350,000 people with an initial CZK 10 million investment and free resources such as a “101 tips” brochure for teachers, creating a rare window to move from policy to classroom practice.

For educators and school leaders seeking hands-on routes into that shift, short applied programs that teach prompt-writing and workplace AI workflows - like Nucamp's AI Essentials for Work - offer immediate, practical skills that map directly to the strategy's human-capital goals and the EU AI Act compliance agenda.

“The artificial intelligence is not just about deploying new technology, but above all, about changing mindsets. The successful use of artificial intelligence must be based on four pillars: trust, data, infrastructure and, above all, people.” - Michal Stachník, General Manager, Microsoft Czech Republic and Slovakia

The National Artificial Intelligence Strategy 2030 (NAIS 2030) positions AI as a national economic and public‑service priority: approved in July 2024, it builds on the Czech Republic's 2019 strategy and steers activity across seven interlinked areas - from AI research and education to legal, security and public‑administration use - while explicitly tying national implementation to the EU AI Act and Digital Czechia goals; the Ministry of Industry and Trade leads coordination and the plan even foresees concrete steps such as a regulatory sandbox, an AI Competence Centre for e‑Government and a CZK 232 million allocation for EU AI Act rollout in 2026–2028.

NAIS 2030 rests on three pillars (EU cooperation, digitisation of public administration, and preparing society and the economy for digital transformation) and aims to strengthen competitiveness, state efficiency and societal resilience; it is deliberately practical - an Action Plan will be updated annually to keep measures like enforcement arrangements, notifying authorities and market surveillance aligned with evolving EU rules.

For full strategy text see the Czech Ministry of Industry and Trade NAIS 2030 overview and the EU AI Watch implementation analysis of NAIS 2030 and its links to the EU AI Act.

Key 2025 snapshot: AI is already woven into Czech students' daily lives - according to a STEM Research Institute survey for Nekrachni, 45% of pupils aged 11–19 have tried AI tools in learning, and among those users ChatGPT dominates (used by 89%) while Photomath follows (43%), with common uses in Czech, foreign languages and maths; yet the same study finds tension in classrooms (34% of pupils said teachers discouraged or banned AI, while 24% had tasks explicitly involving AI).

At the same time broader youth polling shows even stronger uptake: almost nine in ten Czechs aged 12–17 report regular AI use, highlighting a sharp generational gap between savvy students and often under‑prepared schools.

These figures sit alongside national signals - ranges of adult generative‑AI experience are lower - meaning policy, teacher training and simple classroom rules are the urgent levers to turn this raw uptake into safe, curriculum‑aligned learning rather than a patchwork of banned‑and‑borrowed tools; imagine a typical class where nearly half of the students quietly rely on AI for homework while a third face outright bans - this is the practical challenge for Czech education leaders in 2025.

For the full survey details see the STEM Research Institute "How We Learn" survey on Czech pupils' AI use and the Expats.cz article on youth AI usage in the Czech Republic.

Czech higher education is moving from policy to practice with hands‑on programs that stitch technical depth, ethics and industry links into everyday study: the Prague inter‑university prg.ai Minor - bringing together CTU's Faculty of Electrical Engineering and Faculty of Information Technology with Charles University's Faculty of Mathematics and Physics and Faculty of Social Sciences - offers themed blocks (CoreML, PERCEPTION, ROBOT, HUMAN and more), a flexible certificate that fits into regular degrees and open applications through March 21, 2025 (see the prg.ai Minor inter-university AI minor overview).

At the same time, specialist degrees such as Charles University's English‑language Computer Science - Artificial Intelligence master's train students in formal foundations, robotics and machine learning with pathways into research and industry; Czech students can join projects alongside companies whose work has fed improvements in tools like Google Translate, Spotify and Alexa, giving a vivid example of research-to‑product impact.

Together these pathways show two clear adoption patterns in 2025: interdisciplinary minors that scale AI literacy across faculties, and deep technical masters that bolster national R&D capacity and graduate pipelines for Czech schools, labs and ed‑tech partners.

Global evidence shows two clear models for bringing AI into schools: high‑tech scale driven by a mature private sector (the United States) and a balanced, government‑led approach that pairs regulation, data infrastructure and workforce planning (Singapore and South Korea), as mapped in the Oxford Insights Government AI Readiness Index; Stanford's Stanford 2025 AI Index report adds that governments are rapidly expanding AI and computer‑science education but unevenly equipping teachers to use it.

The Czech Republic's NAIS 2030 already mirrors those priorities - strategy, teacher training and data‑ready public services - but the practical gap is visible in classrooms, where student uptake outpaces formal school readiness.

Learning from both models means investing not only in tech and industry links but in governance and open data practices (the same levers middle‑income countries use to close readiness gaps), plus targeted teacher professional development such as a GDPR‑aware AI literacy workshop for Czech staff to turn informal student use into curriculum‑aligned learning; imagine a classroom where policy, training and infrastructure work together so that AI becomes a reliable co‑teacher rather than a banned shortcut.

“An ideal AI ready government is one that has a strong performance in government, in the technology sector and the data and infrastructure,” Stirling said.

Practical classroom work in Czech schools can move quickly from policy to playful, curriculum‑aligned practice: the AI Curriculum from AI for Children supplies 43 ready lessons, printable worksheets and webinars so teachers can scaffold AI from Grade 3 up (picture a class guided by friendly robots Hoo and Ray as an intro to basic models), while subject‑specific materials - for example the Czech‑language lesson “Poetry between prompts” - turn poems into prompts and AI‑generated images for close reading, critical comparison and creative rewrites (a vivid 45‑minute task: pupils generate an image from a stanza and debate whether the picture “understood” the poem).

For civics, the DigiHavel digital human offers nine competence‑based activities that work as a debate partner or interviewer to teach democracy and media literacy, and AI‑powered formative tools such as the Tiny app prototype collect real‑time learner data to feed short follow‑up exercises and reduce teacher marking time.

Combine short in‑class prompt‑writing warmups, a media‑literacy session on deepfakes, and project‑based assessments from the AI Curriculum to keep learning hands‑on and GDPR‑aware; parallel teacher training (in‑school trainers and free guides like Microsoft's “101 tips”) helps turn spontaneous student use into curriculum‑aligned learning rather than ad‑hoc bans.

See the full AI Curriculum for schools, the Czech‑language lesson plan, and Microsoft's AI National Skilling Plan for ready resources and teacher guides.

“Children should ideally learn about artificial intelligence already in primary school, as it better prepares them for the future.”

For Czech beginners in 2025 the clearest start is practical and local: join Microsoft's AI National Skilling Plan (a CZK 10+ million, 350,000‑person drive that partners with Charles University and AI for Children) to access short courses, the free “101 tips” brochure for teachers and targeted retraining for public‑service and business roles; pair that with the Microsoft Learn AI hub's role‑based learning paths (AI fundamentals, business‑user Copilot training, and developer/azure modules) to build stepwise skills; and use educator‑focused materials - AI for educators, the Education AI Toolkit and events like the AI Skills Fest - to turn classroom curiosity into curriculum‑aligned practice.

Start with one concrete step (download the brochure or follow the AI for educators path), set a 30‑day habit of 15–30 minutes on Microsoft Learn, and test what works in a single lesson so AI becomes a co‑teacher rather than a shortcut.

For immediate access see Microsoft's national skilling announcement, the Microsoft AI learning hub, and the Education team's guided resources for teachers.

“The artificial intelligence is not just about deploying new technology, but above all, about changing mindsets. The successful use of artificial intelligence must be based on four pillars: trust, data, infrastructure and, above all, people.” - Michal Stachník, General Manager of Microsoft Czech Republic and Slovakia

For Czech Republic schools and universities the practical backbone for classroom AI is not just flashy apps but secure content management, transparent model governance and targeted teacher tooling: industry analysis warns that half of organisations already run GenAI projects and many cite security and privacy as top challenges, so platforms that centralise content and protect data are critical (see Box guidance on generative AI content strategy).

Equally important are auditability and consent - CalypsoAI guidance on model auditability and GDPR alignment highlights the need to record user‑model interactions, explain decisions and align deployments with GDPR and the EU AI Act to build trust and meet legal obligations.

On the frontline, staff readiness matters: a focused Teacher Professional Development on AI literacy workshop (covering GDPR, the EU AI Act and hands‑on prompt engineering) is a concrete step Czech schools can adopt to turn student curiosity into curriculum‑aligned practice.

Finally, infrastructure choices must be realistic and equitable: the OpenPraxis manifesto for open public infrastructure argues for open, public infrastructure because many institutions cannot afford on‑premise GenAI provision and should not be forced to depend on a handful of hyperscalers - a sharp image for Czech regional schools weighing cloud costs against digital inclusion.

Combine secure platforms, clear logging and compliance, and practical PD to make AI a reliable co‑teacher rather than an unmanaged risk: see Box on secure content management, CalypsoAI on ethical deployment, and Nucamp AI Essentials for Work teacher professional development for ready resources.

“Any sufficiently advanced technology is indistinguishable from magic.”

Governance, ethics and legal compliance are no longer optional for Czech classrooms: the EU AI Act reclassifies many educational tools as high‑risk, bans emotion‑inference systems outright, and pushes schools and universities into formal duties - risk assessments, human oversight, record‑keeping and clear transparency towards students and parents - all layered on top of GDPR obligations (see DLA Piper's legal overview and the Czech regulatory tracker).

Practical implications are sharp: deployers (usually schools) must raise staff AI literacy, keep detailed logs (often six months for high‑risk systems), and be ready to justify datasets, monitoring and human‑in‑the‑loop arrangements; universities that develop or supply AI may be treated as providers with heavier conformity, documentation and quality‑management duties per higher‑education guidance.

The Czech NAIS 2030 and the AI Implementation Plan lay national groundwork - from designating competent authorities (the Ministry of Industry and Trade is in the lead) to a CZK 232 million allocation for EU AI Act rollout - but timing matters: prohibitions on certain systems take effect from 2 February 2025 while many core obligations come into force as part of the wider enforcement timeline (see EU and national trackers).

Bottom line: transform AI from a hidden “cheat engine” into auditable, classroom‑friendly support by combining clear policies, staff training and vendor contracts that enforce transparency and data protection (or risk costly enforcement).

DLA Piper - Navigating the EU AI Act and the AI Watch Czech Republic tracker are practical starting points for administrators and legal teams.

“Deployers of AI systems shall take measures to ensure, to their best extent, a sufficient level of AI literacy of their staff and other persons dealing with the operation and use of AI systems on their behalf …” (Article 4)

Conclusion and next steps for Czech educators are practical and immediate: treat AI as a teachable skill, not an unknowable threat - start with short, curriculum‑aligned pilots, skilling for staff and local collaboration.

Register teachers for focused professional development (two‑day intensives and in‑school PD are widely available), bring free classroom materials like the new AI Dětem curriculum into lessons, and connect with the national scene so schools benefit from shared practice and legal clarity; useful entry points include the research and workshops showcased at Prague Synapse (a forum for neural‑network reasoning) and the wide program of Days of AI and community events catalogued by prg.ai to learn from peers and industry.

For hands‑on staff training that maps directly to workplace skills and prompt literacy, consider applied programs such as Nucamp AI Essentials for Work bootcamp to build prompt engineering and classroom‑to‑career pathways - small pilots, rigorous data‑privacy checks, and regular teacher peer reviews will turn student curiosity into reliable learning rather than ad‑hoc bans.

Above all, link classroom experiments to local research and events (ML Prague, CIIRC workshops) so practice and policy evolve together: one well‑run pilot that preserves privacy and documents outcomes is worth a dozen banned‑tool memos, and it seeds the school‑level evidence leaders need to scale change.

“The most fascinating part was watching how traditional logic-based reasoning methods clashed and connected with those aiming to achieve the same goals using neural networks. This interdisciplinarity was one of the workshop's biggest strengths,” said conference organizer Jan Hůla (CIIRC CTU) about Prague Synapse 2025.