Netherlands AI Job Risk 2026: Which of 9.8 Million Workers Are Most Exposed?

The most AI-exposed occupations in the Netherlands

The Netherlands has built one of the world's most knowledge-intensive economies. Home to Philips, ASML, ING, Shell, and Unilever - all with major AI adoption programmes - the Dutch workforce is heavily weighted toward professional, managerial and technical roles. That concentration is exactly why the Netherlands tops the global AI exposure table at 5.44/10.

General and keyboard clerks sit at the top of the AI risk table at 9.0/10 - the same score as France, Germany and Italy. But in the Netherlands, the most striking figure is the sheer size of the business and administration professional group: 962k workers at 9.9% of the total workforce scoring 8.0/10. No other country we have analysed has this degree of knowledge-worker concentration at the top of the risk table.

Why the Netherlands scores the highest AI average in the world

The Netherlands' 5.44/10 weighted AI average is not simply a product of high top-end scores - it reflects the composition of the entire workforce. The Dutch economy has long punched above its weight in professional services, finance, logistics, and technology relative to its population of 17.9 million. When you look at the distribution of Dutch workers across ISCO-08 occupation groups, a striking pattern emerges: a very large concentration in high-AI-exposure knowledge roles and a very small manufacturing base.

Business and administration professionals at 962k (9.9% of the workforce) is the defining number. These are accountants, finance managers, HR directors, legal specialists and strategy consultants. The Netherlands is home to the European headquarters of hundreds of multinationals - ABN AMRO, Aegon, Randstad, NN Group, and dozens of US technology companies that chose Amsterdam as their EU hub. The people running those European operations are disproportionately in this 8.0/10 AI category.

ICT professionals at 485k (5.0%) add a second major high-exposure group. The Dutch ICT sector is driven by the Amsterdam startup ecosystem, ASML's semiconductor equipment empire in Eindhoven (which has one of the world's highest concentrations of AI and photonics engineers per square kilometre), and the Philips healthcare technology division. These workers write code, build systems, design software architectures - all tasks that AI tools are actively augmenting in 2026.

The business and admin associate professionals group at 682k (7.0%) at 7.5/10 rounds out a combined knowledge-worker exposure that dwarfs most European peers in proportional terms. Add the legal, social and cultural professionals (444k at 7.0/10) and the science and engineering professionals (428k at 7.0/10) and it becomes clear: the Netherlands is an economy almost entirely built on work that sits above the midpoint of AI exposure.

The ICT paradox: building AI tools while facing AI exposure

ICT professionals in the Netherlands score 8.5/10 on AI exposure - the second-highest category - while simultaneously being the people developing and deploying the AI tools creating that exposure. This is a well-documented pattern across high-income technology economies: the builders of AI are also among the most affected by it.

The Dutch ICT sector has seen substantial adoption of AI coding assistants, automated testing frameworks, and AI-generated documentation. GitHub Copilot usage in Dutch enterprise software development has grown rapidly since 2024. The realistic outcome is not mass unemployment of Dutch ICT workers but rather a reduction in team size per unit of software output - each team accomplishes more, and companies hire fewer people for the same function.

The ASML effect is worth naming explicitly. ASML in Eindhoven employs thousands of the Netherlands' most senior engineers in extreme ultraviolet lithography - a domain so specialised that AI tools provide marginal impact on the core physics and optics work. High AI exposure scores for the ICT professional category reflect average task profiles, not the full range of specialisation within the group. Senior engineers at ASML are considerably less exposed than junior software developers at Amsterdam startups doing boilerplate backend code.

The safest jobs from AI in the Netherlands

The Netherlands' safest occupations from AI are concentrated in physical care, cleaning and manual work - and importantly, the personal care worker group at 435k is one of the largest single groups in the Dutch workforce despite scoring only 2.0/10 on AI exposure.

Personal care workers at 435k (4.5% of the Dutch workforce) reflect something structural about the Netherlands. The country has one of Europe's highest proportions of workers in public health and social care - a product of the Netherlands' comprehensive welfare state and its aging population demographics. These workers provide home care, nursing home assistance, disability support and child welfare services. Their work requires physical presence, empathy, situational judgment and trusted relationships with vulnerable people. No current AI system can replicate these qualities at scale.

The assemblers group in the Netherlands is notable for how small it is: only 26k workers (0.3% of the workforce), with the highest robotics score at 8.5/10. The Netherlands simply does not have a large manufacturing assembly sector - unlike Germany (which has a substantial assembler workforce) or the UK. The tiny size of this group is a major reason why the Netherlands' overall robotics average (3.33/10) is low despite some individual groups facing significant robotics risk. It is a feature of the Dutch knowledge economy, not an oversight.

Sales workers at 598k (6.1%) and 5.0/10 AI represent a middle-exposure group that is growing in significance. Dutch retail and B2B sales are increasingly AI-assisted, with chatbots and recommendation engines handling initial customer interactions. The remaining human sales work concentrates on complex, relationship-dependent and high-value transactions.

What this means for Dutch workers

The Netherlands' position at the top of the global AI exposure ranking is a direct consequence of choices made over decades: to build a knowledge-intensive, services-led, internationally oriented economy. Those choices created prosperity. They also created a workforce where the majority of workers sit in occupation groups with above-average AI exposure.

For Dutch workers in business and administration - the 962k at 8.0/10 - the near-term reality is AI-assisted workflows rather than outright replacement. Dutch companies are deploying AI tools for financial analysis, contract review, HR screening, and business reporting at increasing scale. Workers who understand how to direct, validate and supplement these tools will retain value. Workers who only execute the routine tasks that AI now handles are more exposed over a 3-7 year horizon.

The Dutch government's AI policy framework, combined with EU AI Act compliance requirements, creates a regulatory context that slows the most aggressive automation. Large organisations deploying AI in decision-making roles affecting workers face transparency and audit requirements under the EU framework. This provides some buffer but does not halt the underlying shift in task allocation between humans and AI systems.

For anyone considering retraining in the Netherlands, the data points clearly to healthcare and social care as combining low AI risk with strong structural demand from demographics. A care worker in the Netherlands faces 2.0/10 AI exposure in a sector with a documented and growing worker shortage. That combination - low automation risk, genuine labour market demand - is as durable a career position as the Dutch labour market offers.