The Netherlands stands out in Europe for AI adoption, with 95% of organizations implementing AI programs. However, experts caution against getting swept up in overly optimistic forecasts.
Anna Salomons, a labor economics professor at Utrecht and Tilburg Universities, points out that these predictions can be misleading. Many come from large employers who often lead in technology adoption, which doesn’t always represent the broader job market.
Instead of accepting forecasts at face value, it’s crucial to dig deeper. Technology often reshapes work rather than simply replacing jobs. Salomons notes that 60% of today’s positions didn’t exist back in 1940, illustrating how tech creates new roles alongside eliminating others. She also references the hype around self-driving vehicles, which have not rolled out as rapidly as predicted.
“Just a few years ago, there were claims that truck drivers would be out of work in five years,” she says, “but that hasn’t happened. Gradual change eases the transition as retiring workers aren’t always replaced, and newcomers explore different career paths.”
The rise of AI brings its own set of challenges. Workers face concerns about job security and mental health. Research from TNO and the RIVM indicates that while AI can ease physical workloads by taking over repetitive tasks, it can also increase mental strain. Employees now juggle overseeing AI processes, navigating new software, and troubleshooting issues that machines can’t solve.
Wouter van der Torre, a TNO researcher, notes that many organizations overlook how AI reshapes daily work. “We prioritize speed and cost efficiency, but we rarely consider how it impacts people’s ownership and stress.”
AI integration creates a hybrid role for employees. They’re not just performing tasks anymore; they’re supervising and collaborating with intelligent systems. Success in this new landscape demands technical skills, emotional intelligence, and adaptability. Rather than following rigid guidelines, workers now need to engage with AI-generated recommendations, employing a more dynamic decision-making approach.
Salomons emphasizes that workers need more than just a quick AI crash course. Comprehensive training is essential, with a focus on practical exercises, scenario-based learning, and ongoing support, particularly for those less familiar with digital tools. Training should cover fundamental digital skills alongside advanced AI topics.
This brings us to the concept of AI literacy—the ability to understand, interact with, and oversee AI tools responsibly. The European AI Act is stepping in to regulate transparency and accountability in AI systems, mandating that organizations show a baseline level of AI competence among employees, especially in specialized areas. In the Netherlands, educational institutions and corporate training programs are beginning to focus more on data, algorithms, and ethics to build a workforce capable of working alongside AI.
Salomons argues that enhancing AI literacy is vital for using technology effectively and not just as a means to cut costs. She believes we need employees who can critically evaluate algorithm outputs. “We need people who challenge the algorithms, not just follow their lead,” Salomons insists, stressing the importance of understanding how these systems operate.
AI literacy goes beyond coding skills; it involves interpreting results and spotting biases. Salomons believes that understanding AI shouldn’t be limited to a small group of engineers. A successful AI transformation requires a collective understanding among citizens, workers, and decision-makers so that everyone can engage meaningfully with these tools.
Despite fears about impending job losses, Salomons sees a silver lining. She believes that while AI will cause shifts in the labor market, it could also spur growth in new fields and help address labor shortages in high-demand areas. For instance, in healthcare, AI might assist nurses with initial diagnostics and patient management, allowing them to focus on more complex tasks.
However, she warns that transitioning from pilot programs to everyday use can take time and might need governmental incentives for successful integration.
Similar stories play out across logistics, retail, and customer support. AI is streamlining routine tasks, allowing humans to concentrate on problem-solving and personalized service. Yet, this shift can add pressure on employees, as they must navigate increasingly complex challenges that automation can’t handle.
For the Netherlands, the goal is to harness AI while prioritizing human factors. “AI will undoubtedly change how we work,” Salomons acknowledges, “but the focus should be on ensuring that this transformation is inclusive and fair.”
A strong institutional framework in the Netherlands helps buffer against the rapid impacts of automation. Salomons highlights how trade unions and collective agreements empower employees to have a say in how technology is implemented in their workplaces. This collaborative strategy can ease transitions, even if challenges arise.
Additionally, there’s a chance for educational institutions to enhance their teaching methods. “Traditional lectures might not work well for retraining,” Salomons says, “but we’re seeing startups use AI to create personalized learning experiences that meet individual needs.”
As the Netherlands continues to lead in AI adoption, its approach shows that success relies more on the right social and institutional frameworks than merely technological prowess. Balancing technological advancement with worker protections can offer crucial insights into managing change effectively.
Salomons concludes by emphasizing the need to rethink not just what can be automated but what new opportunities might arise and who can be included in these evolving professions. That’s where real innovation lies.
