Dutch workforce faces radical transformation as AI adoption accelerates
While the Netherlands leads Europe in AI adoption, a deeper analysis of the labour market reveals a more nuanced narrative than the apocalyptic predictions of job losses
By
- Kim Loohuis
Published: 21 Mar 2025 14:45
In just five years, only one-third of work in the Netherlands will still be performed by humans, with artificial intelligence (AI) and robotics taking over the majority of current jobs, according to the World Economic Forum’s The future of jobs report 2025.
While the Netherlands leads Europe in AI adoption, with 95% of organisations running AI programmes, labour market experts warn that these dramatic predictions should be cautiously viewed.
“These kinds of predictions are quite difficult to make,” said Anna Salomons, professor of labour economics at Utrecht University and Tilburg University.
“The WEF study is based on surveying large employers, who often run ahead of smaller companies in adoption. What one company expects doesn’t necessarily reflect the entire economy.”
Rather than accepting these projections at face value, a closer examination reveals a more complex narrative of technological change. Historical patterns suggest that technological disruption is rarely a straightforward replacement of human labour, but instead a profound reshaping of work itself.
Salomons cited her own research, which shows 60% of today’s employment is in types of jobs that did not exist in 1940, highlighting how technology transforms and creates work rather than only eliminating it. She pointed to previous technological predictions, such as self-driving vehicles, that failed to materialise as quickly as expected.
“A few years ago, there were predictions that truck drivers would all be out of work within five years,” said Salomons. “That hasn’t happened. It’s less painful when change happens more gradually – people retiring aren’t replaced, and new labour market entrants choose different careers.”
Workplace challenges grow
The introduction of AI tools triggers various concerns for workers, ranging from job security to mental well-being. Recent studies by the Netherlands Organisation for Applied Scientific Research (TNO) and the Dutch National Institute for Public Health and the Environment (RIVM) show that AI can lighten physical workloads by delegating repetitive or strenuous tasks to machines. At the same time, employees risk facing a heavier cognitive load. They must supervise these AI-driven processes, adapt to new software interfaces, and resolve exceptions that machines cannot handle.
Wouter van der Torre, a researcher at TNO, warned in Dutch daily newspaper AD that organisations often overlook how AI alters daily tasks. “We focus on faster or cheaper production, which is, of course, the primary driver of innovation, but we seldom ask how it affects people’s sense of ownership or stress levels,” he said.
This observation echoed the findings from numerous interviews with workers in AI-augmented roles, who have reported that tasks become more complex even as specific essential duties are automated.
The cognitive dissonance created by AI integration goes beyond mere task reallocation. Employees find themselves in a hybrid role: part supervisor, part collaborator with intelligent systems. This shift demands not just technical skills, but also emotional intelligence and adaptability. Where once workers followed clear procedural guidelines, they must now interpret and negotiate with AI-generated recommendations, requiring a more dynamic and critical approach to decision-making.
Therefore, the success of AI integration depends on comprehensive reskilling and ongoing support. Salomons emphasised that a quick crash course on AI is not enough to equip workers for the pace of change. She called for multi-layered training programmes and on-the-job learning that includes practical exercises, scenario-based learning and ongoing mentoring, especially for those who may be unfamiliar with digital tools. Rather than focusing solely on advanced AI subjects, such programmes can address fundamental digital skills and problem-solving capabilities.
AI literacy gap
This notion of inclusivity is tied closely to AI literacy, which refers to people’s ability to responsibly understand, interact with and oversee AI tools. The European AI Act, which aims to regulate transparency and accountability in algorithmic systems, demands that companies demonstrate a baseline of AI competence among their employees in specialised departments and potentially across entire organisations. In the Netherlands, educational institutions and corporate training programmes are starting to focus on the fundamentals of data, algorithms and ethics, aiming to build a workforce that can collaborate effectively with AI.
Salomons said expanding AI literacy is essential if technology is to be used in service of people rather than as a blunt instrument of cost reduction. She cited examples of how AI can improve day-to-day tasks when workers comprehend its limitations. “We need employees who can question the output of algorithms and flag errors, not just passively follow whatever the machine says,” added Salomons. “That requires a deeper understanding of how these systems work.”
She said AI literacy is not merely about coding skills, but also interpreting results and recognising potential biases.
“It’s not enough for an elite group of engineers or data scientists to know how AI functions,” said Salomons. “A truly inclusive AI transition requires a baseline of understanding among citizens, employees, managers and policymakers. That way, people can engage meaningfully with these tools in their workplaces or communities.”
Future of work
Despite the dramatic headlines about looming job losses, Salomons was relatively optimistic. In her view, AI will not only lead to labour displacement and labour market adjustments, but can also catalyse job growth in emerging fields and help alleviate labour shortages where demand is high.
She referenced the healthcare sector, where AI tools could help nurses in preliminary diagnostics, triage and care management, while reducing administrative work. Rather than eliminating nurses, such technology could elevate their roles by allowing them to manage more complex tasks with AI systems. However, Salomons cautioned that the path from pilot projects to day-to-day adoption can be lengthy, and may require governments to incentivise these types of applications.
Similar stories are unfolding in logistics, retail and customer support, where chatbots and automation speed up routine queries. Humans then focus on problem-solving and personalised service. This model can be beneficial, but also introduces new pressures for employees who must handle complex scenarios that automation cannot resolve independently. The resulting spike in mental strain underscores the importance of supportive corporate cultures and adequate staffing.
The Netherlands aims to steer AI adoption in a way that boosts productivity while keeping the human dimension at the core. “There’s no denying that AI will transform how we work,” said Salomons. “The debate shouldn’t be about whether that happens, but about how inclusive and equitable that transformation can be.”
Balancing technology and workers
In the Netherlands, a strong institutional framework provides some measure of insulation against the adverse effects of rapid automation. Salomons noted that trade unions, work councils and collective bargaining agreements help to ensure that employees have a voice in how technology is adopted in their organisations. This collaborative approach does not guarantee a frictionless transition, but does offer pathways for workers to negotiate how AI might reshape their jobs.
There is also high potential for educational institutions to improve how instruction is delivered. “Traditional lecture-based learning isn’t necessarily effective for people who need to retrain,” said Salomons. “But we’re seeing startups using AI to create more personalised training programmes, adapting to individual learning needs, which can complement in-person instruction.”
The Dutch experience suggests that successful AI adoption depends not just on technological capability, but on creating the right institutional and social conditions. As the country continues to lead in AI adoption, its balanced approach offers valuable lessons in managing technological transition while maintaining worker protection and job quality.
“The key is to think not only about what can be automated, but about what new things we can now do, or what new groups of people we can now bring into certain professions,” said Salomons. “That’s where real innovation happens.”
