The Complete Guide to Using AI in the Education Industry in Denmark in 2025

This guide matters because Denmark's 2024–27 AI push is already reshaping classrooms: a new national strategy funds DKK 62.5 million and the public–private AI Competence Pact aims to upskill 1 million Danes, creating an open sandbox, language-model infrastructure and a centre to advise schools on safe, Danish-language AI tools (see Denmark's new AI strategy).

Schools face urgent choices - how to turn risks like exam cheating and “digital dependency” into learning opportunities - illustrated by nationwide conferences and a 350-person Aarhus University event that stressed teacher professional development and change management (read the Aarhus University coverage).

For practical reskilling, school leaders and educators can pair policy with hands-on training such as Nucamp AI Essentials for Work bootcamp registration (15 weeks) to master prompts, workplace use cases, and classroom-ready workflows that keep humans in the loop while leveraging AI's efficiency.

This guide maps policy, pedagogy and pilot steps so Danish education can be both ambitious and equitable in 2025.

“The real disruption isn't in how we teach, but in how our students' minds are reshaped by constant AI interaction.” - Jeppe Klitgaard Stricker

Key 2025 indicators show Denmark as a busy testbed for classroom AI rather than a quiet watcher: Denmark hosts ICAIE‑25 Roskilde conference details on 6–7 June 2025, a focal point for researchers and ed‑tech pilots, while practical tools are entering classrooms - the new micro:bit CreateAI hands-on ML tool lets students train and code a working ML model and “build an AI‑powered piece of tech” in about 90 minutes, bringing machine learning into hands‑on lessons.

UNICEF's Tinkering with Tech added AI literacy from mid‑2025, signalling international momentum for curriculum change, and funding mechanisms are available at scale (Innovation Fund Denmark supports projects from ~DKK 50,000 up to several million).

Those numbers translate into tangible activity: international conferences, classroom toolkits tested in playgrounds and labs, and grant lines that make school pilots feasible - so school leaders can map clear pilots with measurable inputs (time, device, grant size) rather than vague promises.

For more on the Roskilde conference see ICAIE‑25 Roskilde conference details and to explore the classroom tool, try micro:bit CreateAI hands-on ML tool; for grant details see government funding guides.

“We are currently caught between two points: we are worried that artificial intelligence will lead to cheating on exams, loss of skills, and teacher job cuts – but we are also enamored with the fantastic possibilities it offers for enhancing teaching and preparation.” - Agi Csonka

Denmark in 2025 looks well placed to be an AI-ready education market but with a clear "so what?" - strong pipes alone don't guarantee equitable classroom impact.

The country's high‑quality digital infrastructure and a EUR 1.07 billion Digital Decade roadmap underpin fast adoption, while a new national AI strategy (DKK 62.5m) plus the public‑private AI Competence Pact to upskill 1 million Danes are concrete policy levers that make Danish schools fertile for pilots and scale-ups (see the Denmark 2025 Digital Decade country report and the Danish national AI strategy and AI Competence Pact overview).

Yet gaps matter: R&D and advanced innovation are clustered in a few universities and large firms, SMEs and many schools still struggle to recruit ICT specialists, and national guidance is evolving - Denmark proposed its first AI bill in February 2025 to sit alongside the EU AI Act, which will shape procurement, liability and public‑sector pilots (legal context summarized in Bird & Bird's practice guide).

Practically, that mix means Danish education leaders can draw on strong infrastructure and funding while planning pilots that explicitly close the skills and SME adoption gaps; otherwise the country risks uneven benefits and the behavioural risks flagged in recent debates, from exam integrity to rising "digital dependency."

“The real disruption isn't in how we teach, but in how our students' minds are reshaped by constant AI interaction.” - Jeppe Klitgaard Stricker

Denmark has moved quickly to translate the EU AI Act into national practice: a draft bill was introduced on 26 February 2025 and Denmark adopted implementing legislation in May 2025 that is set to enter into force on 2 August 2025, formally supplementing the EU AI Regulation and crystallising which AI uses will be prohibited or tightly controlled (see the Chambers practice guide and an early implementation summary).

The law names the Agency for Digital Government as the national market‑surveillance authority and single point of contact, with the Danish Data Protection Agency and the Danish Court Administration covering biometric/data‑protection and judicial uses respectively, so organisations across sectors must now plan for coordinated oversight.

Practical pieces are already in place: a regulatory sandbox has funded pilots (Tryg Forsikring's injury‑documentation assistant and Systematic's healthcare documentation work were in the first round), and further sandbox rounds opened in 2025 to guide GDPR‑aligned development.

Enforcement powers are concrete - authorities can demand technical documentation, carry out on‑site inspections, impose injunctions and fines - which means schools and education providers should map their AI use, document data sources and human‑in‑the‑loop safeguards, and update procurement/contracts to cover liability and data governance before pilots scale.

Across Europe the picture is mixed: Denmark is a clear early adopter in the market - 28% of Danish companies reported using AI in 2024, nearly double the EU average, and a large share of big Danish firms are already deploying AI - so the country functions as a practical testbed for classroom pilots and public‑sector projects (Invest in Denmark report: Denmark tops Europe in AI adoption), yet that momentum masks a worrying policy gap at the institutional level.

A Media & Learning survey found that roughly 80% of participating higher‑education institutions across six countries - including Denmark - either lack formal AI policies or are unsure they have them, signalling a disconnect between fast uptake and governance support (Media & Learning study: AI policy adoption in higher education).

At the same time, education systems are reacting in very different ways: some Danish schools have pulled back from ubiquitous devices - famously locking pupils' phones in a safe at Trongårdsskole to curb distraction - mirroring national debates on balance and wellbeing reported across Europe (Euronews report: Danish schools lock smartphones during the school day).

The takeaway for Danish leaders is clear: Denmark's infrastructure and business readiness create rare opportunities for scaled pilots, but international comparisons show that adoption without clear institutional policies, teacher training and ethical guidance risks uneven benefits - so schools should pair ambitious pilots with fast policy work, concrete staff upskilling and accountable governance if national leadership is to translate into better, fairer classroom outcomes.

“We were constantly disturbed by notifications and all kinds of distractions from all kinds of apps and even parents calling in the middle of lessons.” - Bent Povlsen, Trongårdsskole

Classroom pilots in Denmark show a clear bias toward hands‑on, student‑centred practice: the national DR ultra:bit programme has woven micro:bit projects into core lessons and popular media, reaching about 90% of Danish fourth‑graders and over 1,400 schools so far, so teachers can turn coding into creative projects - from humidifiers to the now‑famous “garbage‑y” fish that collects rubbish from Aarhus harbour - making tech tangible and meaningful for 9–12 year‑olds (see the DR Ultra:bit impact report for Denmark).

That practical design matters because teachers are not expected to be tech specialists; instead DR built short, subject‑linked exercises, an interactive intro course and a travelling taskforce offering free three‑hour workshops that raised teacher confidence and sparked curriculum innovation.

These pilots pair well with student‑centred pedagogy - where learners help choose problems and demonstrate learning - so classroom AI and maker activities become opportunities for agency rather than passive consumption (read the student‑centred learning primer for teachers).

For leaders planning pilots, the ultra:bit evidence is a useful blueprint: keep tasks simple, embed technology into subjects, fund short teacher training bursts, and measure both student engagement and teacher readiness before scaling.

Assessment in Denmark is moving from prohibition to experiment: from 2026 selected high schools will pilot a model where students may use “all available tools, including generative AI” during the one‑hour preparation window for English oral exams, then deliver their presentation live to an examiner - an hour with AI at their fingertips followed by an in‑person performance that tests speaking skill, not device mastery (see the Complete AI Training summary and reporting in The Straits Times).

To guard standards the written English test will still require handwriting for certain sections, preserving independent language practice and limiting overreliance on digital aids, and the programme is intentionally voluntary so schools can join as controlled pilots.

For leaders and teachers this means assessment design must document permitted tools, rehearse examiner protocols, and pair digital preparation with explicit rubrics that reward original language use and oral competence rather than polished, AI‑generated phrasing.

“With students growing up in both analogue and digital worlds, we need to ready them in the best way possible for the reality they will encounter after their schooling.” - Mattias Tesfaye

Denmark's upskilling story in 2025 is firmly a national project: the public‑private AI Competence Pact aims to raise the AI skills of 1 million Danes by 2028, backed by the government's national AI strategy and a DKK 62.5 million funding framework to build Danish model infrastructure, sandboxes and teacher support (see the national strategy overview), while major partners are already stepping up - ATP, the DKK689bn pensions giant, is a founding partner and has signalled it will help scale training across the labour market and public sector (read IPE on ATP's role).

The pact bundles industry courses (Microsoft is providing a free online learning environment), university programmes such as the Inge Lehmann talent fund, and targeted inclusion measures for women, people with disabilities and citizens with shorter educations, so pilots can combine short, practical modules with workplace projects and clear progression paths; the result is a concrete pipeline from classroom PD to on‑the‑job re‑skilling, not just abstract promises.

The vivid implication: Denmark isn't merely offering courses - it's mobilising pension funds, tech firms and universities in one coordinated push to put AI competence into everyday jobs and schools, making workforce development both broad and measurable.

“SDU co-founded Denmark's AI Skills Pact because we have a responsibility to enhance young people's foundational AI competencies and AI literacy.” - Peter Schneider‑Kamp

Legal and procurement choices now shape whether AI pilots in Danish schools remain innovative or become liability traps: the Danish Data Protection Agency (Datatilsynet) is not just an enforcer but a hands‑on adviser - publishing guidance, podcasts, an education package and even a data concern mailbox - so school leaders should use its resources early (Datatilsynet guidance for Danish schools on AI and data protection).

Recent scrutiny shows the stakes in practice: the DPA is investigating whether use of Google Workspace for Education in municipal schools complies with Danish rules, a live reminder that popular platforms are not automatically permitted (Danish DPA investigation of Google Workspace for Education compliance).

Institutional rules matter too - universities like SDU require researchers to register projects before collecting personal data and forbid external tools that store data offsite unless a formal data‑processing agreement is in place - an approach that schools and municipalities should mirror in procurement and vendor contracts (SDU legal and GDPR guidance for research data management).

Practically, document your data flows, appoint or consult a DPO, demand data‑processing agreements, and treat procurement as a privacy audit; with GDPR's heavy penalties and wide territorial scope, these steps turn compliance from a box‑tick into a protective framework for safe, accountable AI in the classroom.

Cybersecurity is now a core part of any Danish school or university AI rollout: follow the national playbook by using the Danish Centre for Cyber Security official guidance to harden systems, map supplier risk and log events (Danish Centre for Cyber Security official guidance), align incident and data‑breach procedures with GDPR (notify the Danish regulator within 72 hours) and the evolving NIS/DORA rules summarised in the ICLG guide to cybersecurity laws and regulations in Denmark (ICLG guide to cybersecurity laws and regulations in Denmark), and make staff readiness non‑negotiable through focused training such as the Nucamp Cybersecurity Fundamentals 15-week bootcamp syllabus (Nucamp Cybersecurity Fundamentals 15-week bootcamp syllabus) to build baseline skills and tabletop response practice.

Practical checklist items: classify AI data flows and run DPIAs for tools that send data offsite; require data‑processing agreements and supplier security evidence; enable multi‑factor authentication and adaptive phishing training (the human layer still drives most breaches); keep tamper‑proof logs so CFCS/authorities can reconstruct incidents; document human‑in‑the‑loop safeguards for pedagogical AI uses; and test incident playbooks with realistic phishing and ransomware drills - remember, modern phishing and AI‑amplified social engineering can scale rapidly (real‑world exercises show high click volumes without behaviour change).

These steps turn compliance into a resilient framework that protects students, preserves exam integrity and keeps pedagogy in control rather than chasing crises after the fact.

“In the near future, AI will power significantly more phishing attacks - everything from text‑based impersonations to deepfake communications will become cheaper, more convincing, and more popular with threat actors.” - Mika Aalto, Hoxhunt