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

In 2025 the Netherlands is steering AI in education toward a human‑centred, skills‑first future: the government's Strategic Action Plan for AI sets the course with ministries and the Dutch AI Coalition partnering to boost AI education and skills, while legal frameworks such as the EU AI Act and an active Data Protection Authority signal stronger oversight for transparency and bias mitigation; practitioners can see this balance of opportunity and caution echoed in calls to

preserve human agency

on International Day of Education 2025.

For Dutch schools and campuses that want practical next steps - teacher upskilling, transparent procurement and classroom pilots - this means combining policy-aware governance with hands‑on training like Nucamp's AI Essentials for Work to teach prompt writing and workplace AI skills, and using guidance from the OECD plan and sector reports to align pilots with national priorities and rights‑based safeguards.

In 2025 Dutch classrooms and campuses moved from talk to tangible change as the EU's risk‑based rulebook started reshaping practice: the AI Act's early prohibitions and new AI‑literacy duties kicked in from 2 February 2025, banning intrusive uses such as emotion recognition in education and forcing organisations to upskill staff, while a second wave of governance and GPAI obligations became effective on 2 August 2025 (the European Commission's AI timeline explains the staged rollout), prompting Dutch authorities and institutions to prioritise transparency, DPIAs, procurement clauses and clearer vendor documentation; at the same time the Dutch Data Protection Authority signalled tougher oversight on algorithmic fairness and auditing, so schools that pilot generative tools must pair hands‑on teacher training with legal checks, inventorying systems and clear human‑in‑the‑loop controls to avoid hefty penalties and reputational risks (see Dutch DPA guidance and commentary on GPAI provider obligations for practical steps).

“The timetable for implementing the Artificial Intelligence Act (EU AI Act) remains unchanged. There are no plans for transition periods or postponements.”

The Netherlands' AI strategy for education stitches national ambition to practical action: built on three pillars - capitalising on societal and economic opportunities, creating the right conditions (education, skills and infrastructure) and strengthening ethical foundations - the plan backs large public‑private efforts such as the Netherlands AI Coalition and the AiNed programme to scale AI R&D and classroom readiness, while targeting human capital with reforms across primary, secondary and higher education plus lifelong learning funds like the STAP scheme; concrete investments include multi‑year programmes and targeted grants (see the EU's Netherlands AI Strategy Report) and recent government moves to support responsible generative AI - fueling projects like GPT‑NL and channeling National Growth Fund resources to applied AI facilities - to keep innovation grounded in public values, transparency and human‑centred safeguards (read the Dutch vision on generative AI).

This strategy is deliberately pragmatic: it couples curriculum and teacher upskilling with data‑infrastructure plans and an Algorithm Register to normalise explainability, so Dutch institutions can pilot tools with clear legal and ethical guardrails rather than retrofitting compliance later.

“We wish to retain the values and prosperity of the Netherlands. ... By stating our principles now, we will maintain control in the future.”

Which country is leading AI and introducing it to education? The Netherlands is a surprising frontrunner: although it represents just 2.8% of Europe's population, it accounts for about 8% of the continent's AI talent, with Amsterdam alone hosting roughly 7,000 specialists - an unusually dense talent cluster that schools and universities can partner with to run meaningful pilots; at the same time Dutch organisations are among Europe's most active adopters (reported at 95% running AI programmes), backed by targeted public investment of about €276m and a pragmatic ecosystem that blends startups, industry and research institutions, so campuses can move quickly from experiments to scaled automation and learning tools (see the IO+ talent analysis and the AI automation report for the Netherlands); the big caveat is public trust - surveys show relatively low citizen acceptance - so for education the opportunity is clear but success depends on coupling high technical capacity with teacher training, governance and well‑designed pilots that demonstrate real learning gains rather than hype.

“We were delighted to bring together leaders from Russell Group universities and their counterparts from the Netherlands to discuss issues around the use of generative AI in higher education.”

The Netherlands is well‑placed for educational AI thanks to a lively ecosystem - about 402 AI‑producing companies in 2024, large regional clusters in Noord‑ and Zuid‑Holland, and a surprisingly large pool of learners (AI‑broad enrolment reached nearly 104,000 in 2023/24) that supplies classrooms and campuses with digitally literate students - but the picture is mixed for schools and universities that must turn this potential into reliable, equitable outcomes.

Strengths include rapid growth in AI education pathways and a steady pipeline of vacancies (many posted by universities), plus firms increasingly adopting off‑the‑shelf AI tools; challenges include uneven regional concentration, the reality that most AI companies are SMEs with limited scale, and a skills gap and adoption barrier - around three‑quarters of organisations that considered AI cited “lack of experience” as the main reason they hadn't implemented it.

Political and market headwinds also matter: international student growth has slowed, which could tighten the talent pipeline that Dutch campuses rely on. For pragmatic educators, the takeaway is clear: leverage the strong supply of AI learners and local industry ties while investing in teacher upskilling, practical pilots and procurement safeguards so promising capacity doesn't remain fragmented or underused (see the Dutch AI Monitor and recent Nuffic analysis for the data behind these trends).

“The decline is not surprising at all – none of the regulations changing English language programs to be taught in Dutch have actually happened yet – but this is a gut reaction by the market based on the perception of studying in the Netherlands.”

Practical AI use in Dutch classrooms is already concrete and classroom‑ready: SURF is actively testing responsibly designed tools like EduGenAI and running pilots to help institutions embed adaptive learning and safe workflows across campuses, while modular digital learning environments tested with partners such as OAT's TAO platform show how assessment, content and tools can plug together in a next‑gen ecosystem (SURF AI in Education overview, OAT TAO chosen for SURF pilot program).

On the classroom level, expect three high‑impact use cases: always‑on, multilingual AI tutors that provide on‑demand practice and explanations (imagine a student getting a clear phrasal‑verb example at 2 a.m.); teacher‑facing copilots that speed lesson design and nudge pedagogical moves; and assessment integrations that automate routine marking while preserving human judgement.

Evidence from a randomized trial of a Human‑AI tutoring approach (Tutor CoPilot) found measurable learning gains - about a 4 percentage‑point increase in mastery and outsized benefits for students of less‑experienced tutors - at a low per‑tutor cost, showing these systems can scale expertise rather than replace it (Tutor CoPilot randomized trial (Human-AI tutoring study)).

For Dutch campuses the operational takeaway is practical: pair pilots of tutors and adaptive resources with clear guardrails (data inventories, instructor training and human‑in‑the‑loop checks), measure real learning gains, and use SURF's collaborative testbeds to avoid vendor lock‑in and protect equity as these tools move from experiments into everyday teaching.

Dutch institutions adopting AI must treat legal, data‑protection and procurement tasks as front‑line classroom safety: under the GDPR schools have a duty of accountability (register and update processing activities, be ready to demonstrate technical and organisational measures) and must give pupils and parents concise, simple and accessible information about how data are used - remember that children are particularly vulnerable and schools must verify a pupil's identity on registration (see the Dutch Data Protection Authority guidance on use of personal data in education).

Any AI feature that scores, profiles, automates decisions or handles sensitive data will usually trigger a Data Protection Impact Assessment (DPIA): carry out a DPIA before collection, treat it as an ongoing process, and consult the AP if residual risk remains (practical DPIA steps are summarised by the Dutch government DPIA guidance for data protection impact assessments).

Procurement must require written agreements with vendors that store or process pupil data, and public bodies should register a Data Protection Officer where required; operational advice and templates for registers, consent and DPIA workflows are available from university compliance guides such as VU's GDPR resource (VU University GDPR compliance guidance and templates).

Practical takeaway: inventory every system, do the DPIA up front, bake contract clauses and vendor documentation into procurement, and explain privacy to learners in plain language so rights are meaningful, not just a checkbox.

Dutch schools and universities should treat governance as operational glue: start by mapping every AI use (an AI inventory) and formalise it in an AI register, classify tools by the EU AI Act risk levels and prioritise high‑risk systems for oversight and DPIAs, while scheduling proportional AI literacy training now that staff training is a legal duty from February 2025; crucially, appointing an AI compliance lead - preferably by August 2025 - turns diffuse responsibility into a single point of coordination who keeps the register current, runs review cycles and owns vendor contracts and appeals processes (the ISC Research primer lays out these practical steps and timelines).

Pair that internal backbone with external collaboration: tap into co‑creation networks such as the National Education Lab AI (NOLAI) to test prototypes, involve teachers and researchers in pilots, and bake the Dutch “human‑centred” Toolbox principles into procurement and board reporting so public values and explainability are front‑and‑centre.

Operational checklists should include clear policies for human‑in‑the‑loop decisions, documented oversight of automated grading or admissions models, routine fairness checks and a remediation pathway - remember the regulatory stakes (fines can reach the tens of millions) and the reputational cost of getting it wrong - so a pragmatic, documented cycle of assess → review → comply keeps innovation legal, transparent and centred on learning outcomes.

“With a structured, step‑by‑step approach, we can turn regulatory challenges into opportunities for better, more thoughtful AI integration in education.”

Begin with a clear, low‑friction inventory: catalogue every classroom and campus system in a single register (think library catalogue for tools) and immediately classify each item by EU AI Act risk level so you know which systems need the most scrutiny; next, mandate a DPIA for any tool that scores, profiles or handles sensitive pupil data - remember the Dutch and EU guidance flags voice and image generation as potentially high‑risk and likely DPIA triggers - and treat DPIAs as living documents you update through the pilot phase (see the AI Act overview for timelines and risk rules).

Appoint an AI compliance lead to own the register, procurement clauses and vendor paperwork, and roll out role‑based AI literacy training to staff now that training duties are in force; require contracts to lock in lawful training data, explainability, human‑in‑the‑loop guarantees and mechanisms to uphold data subject rights as signalled in recent DPA guidance on generative models.

Pilot small, measure real learning gains, and scale only after independence checks and vendor transparency are proven - this staged approach turns regulatory obligations into practical guardrails, protects pupils, and keeps innovation classroom‑centred rather than compliance‑after‑the‑fact (EU AI Act rules and timeline - Netherlands official guidance, Dutch DPA preconditions for generative AI (data protection authority guidance), DPIA risks for AI-generated voice and visuals - TechGDPR guidance).

Conclusion: Dutch educators have a clear playbook for 2025 - treat regulation as a roadmap and practice as the proving ground. Start by meeting the EU AI Act's AI‑literacy duty (staff training is legally required from Feb 2, 2025) and use local, low‑risk opportunities to build skills and evidence: join regional events and hands‑on modules such as Maastricht University's June programme (from prompt workshops to AI tutors and ethics sessions) to convert policy into classroom-ready practice, pilot small (think an AI prompting hackathon that leaves teachers with a live prompt library), and make DPIAs, vendor clauses and a central AI register non‑negotiable before scaling.

Pair these steps with role‑based AI literacy for procurement teams and instructors so tool choices are pedagogically justified and auditable; practical upskilling can be accelerated with targeted courses like Nucamp's Nucamp AI Essentials for Work bootcamp syllabus for prompt writing and workplace AI skills.

For legal clarity and implementation tips on required staff training and organisational duties, see the government guidance on Dutch government guidance on AI literacy under the EU AI Act, and for local collaboration and inspiration browse the Southeast‑Netherlands event listings at Maastricht University June AI activities for educational institutions; small, well‑measured pilots plus transparent governance will turn regulatory pressure into better, fairer learning.

“Providers and deployers of AI systems shall take measures to ensure, to their best extent, a sufficient level of AI literacy of their staff…”