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How is AI really changing the nature of work? Five lessons from EuropeThe increasingly rapid adoption of Artificial Intelligence (AI) in workplaces around the globe has brought renewed urgency to an age-old question: how will technology change the nature (and future) of work? In 2020, before the recent acceleration in generative AI adoption, the Center launched a research partnership with leading European think tank <a href="https://www.bruegel.org/future-work/future-work-and-inclusive-growth-europe" rel="noopener noreferrer" target="_blank" class="">Bruegel </a>to study the future of work, AI, and the broader impact of technology and digitalization. The context has changed significantly since then, but the questions at the heart of that research remain deeply relevant today: how technology reshapes jobs, what skills workers need, how job quality can be protected, and how institutions can ensure that innovation expands opportunity rather than deepens exclusion.Evidence from Europe suggests that AI is not simply changing how many jobs exist — it is changing what jobs are available, how work is organized, the skills that matter, and whether people will be able to move into better opportunities as the economy shifts. And while the global future of work is still uncertain, these lessons from Europe offer a useful grounding point for understanding what still applies, what questions remain open, and how institutions can stay anchored in worker well-being during a period of rapid AI advancement.Below are five key lessons drawn from the Center’s research partnership with Bruegel, to resurface some useful – and still relevant – findings from this body of work. Together, they show why this earlier work continues to resonate today: it identified the questions that still define the transition — to what extent technology will impact people, replace certain jobs, how work will change, what protections and pathways workers need, and how innovation can be guided toward more secure, inclusive, and human-centered outcomes.

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1. AI is transforming jobs by changing tasks, not simply eliminating occupations.Bruegel’s research shows that AI is more likely to redesign work than simply erase it. Earlier waves of automation primarily affected routine, middle-skill tasks. However, the age of AI is different, as AI can perform cognitive tasks across a wider range of roles – including administrative, customer-service, and some lower-skill jobs that were once thought to be less exposed.<a href="https://www.bruegel.org/event/work-future-how-are-new-jobs-created-and-what-are-implications-labour-markets" rel="noopener noreferrer" target="_blank" class="">Bruegel’s discussion</a> of “new work” reinforces this: technology does not operate on a fixed set of occupations, but rather, it reshapes the task mix of work itself. Workers may spend less time on repetitive processing and more time on judgement, relationship-building, or problem-solving – and in higher-skill fields, productivity gains may also create new tasks and roles that will require different capabilities than the jobs being disrupted. The future of work will therefore depend not just on whether AI is available, but on whether firms and workers can harness it effectively.

2. Job quality must be treated as a core measure of success.Beyond income, a job shapes people’s well-being, autonomy, security, and sense of dignity – and is part of the critical foundation for financial health. That is why job quality must be central to any conversation about AI and the future of work.Technology can improve job quality when it makes work safer, supports better decisions, or frees people to focus on higher-value tasks. But it can also make work worse – automated people management or scheduling, and excessive monitoring can increase stress, reduce autonomy, and weaken trust between workers and employers.Using a <a href="https://www.bruegel.org/working-paper/risks-job-quality-digital-technologies-are-industrial-relations-europe-ready" rel="noopener noreferrer" target="_blank" class="">framework of seven job-quality domains</a> — pay, working-time quality, prospects, skills and discretion, work intensity, social environment, and physical environment — Bruegel examined how “<a href="https://www.bruegel.org/working-paper/risks-job-quality-digital-technologies-are-industrial-relations-europe-ready" rel="noopener noreferrer" target="_blank" class="">robot shocks</a>” (measurable increases in workers’ exposure to robots) affected job quality. It found that some negative effects were stronger where collective bargaining was below the median, reinforcing the importance of worker voice and human-centered design. Additionally, <a href="https://www.bruegel.org/working-paper/hidden-inequalities-digitalisation-post-pandemic-context" rel="noopener noreferrer" target="_blank" class="">digitalization can affect less visible dimensions of work</a>, including social interaction, creativity, and innovation – especially as platform and remote work become more common.

3. Skills are becoming the main pathway to resilience and mobility.As AI changes tasks, skill development and training become the bridge between disruption and opportunity. Workers will need continuous learning, practical pathways into new roles, and support to build skills that complement technology to thrive in the changing workplace.Europe faces a <a href="https://www.bruegel.org/policy-brief/what-holding-back-artificial-intelligence-adoption-europe" rel="noopener noreferrer" target="_blank" class="">significant reskilling challenge</a>. Bruegel finds that firms are constrained not only by access to technology, but also by human capital, data availability, funding, basic business digitization, and technological uncertainty. These barriers show that skills are not only essential to worker resilience; they are part of the infrastructure that determines whether firms can adopt and use AI effectively.The most valuable skills will not be purely technical. Workers will need digital literacy and AI fluency alongside the human capabilities that make technology useful: critical thinking, creativity, communication, ethical judgment, and the ability to work with technology.Without equitable access to those skills, AI could widen existing inequalities. Workers and firms with stronger digital capabilities will be better positioned to capture the benefits, while others may remain in roles with fewer pathways to advancement. Skills-based hiring, micro-credentials, and workplace learning can help make opportunity less dependent on formal degrees — but only if they are accessible across sectors, role types, and job levels.

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4. Mobility will determine whether workers can reach the jobs AI creates.Although AI is also creating new jobs, it is important to recognize that those jobs may not appear in the same sectors, regions, or countries where old ones are disrupted. That makes mobility — occupational, geographic, and social — a central issue for inclusive growth.Workers need support to move from declining tasks into growing ones through career guidance, access to training, and smoother transitions between sectors. In Europe, mobility also has a cross-border dimension: simplifying the recognition of professional qualifications, supporting skilled migration, and reducing barriers to working across EU countries can help address talent shortages and regional mismatches. Without deliberate support, workers with more resources, stronger networks, and higher levels of education will be better positioned to move into new opportunities, while others may be left in lower-quality jobs or excluded from the gains of technological change.<a href="https://www.bruegel.org/policy-brief/blending-physical-and-virtual-hybrid-model-future-work" rel="noopener noreferrer" target="_blank" class="">Bruegel’s research on hybrid work</a> adds another dimension to the question of mobility. Remote and hybrid work can make jobs more geographically accessible, but only if safeguards ensure that remote, hybrid, and on-site workers are treated equally and have comparable career opportunities

5. Europe’s central lesson is that the future of work is a governance choice.AI will continue to change work. But the direction of that change is not predetermined. Europe’s experience shows that policy, institutions, employers, and workers all shape whether AI leads to better jobs, or more precarious ones. The opportunity is significant but not assured: Bruegel finds that firms using AI see <a href="https://www.bruegel.org/policy-brief/what-holding-back-artificial-intelligence-adoption-europe" rel="noopener noreferrer" target="_blank" class="">productivity gains of 3% to 4%</a>, while wider adoption could lift European economic activity by <a href="https://www.bruegel.org/policy-brief/what-holding-back-artificial-intelligence-adoption-europe" rel="noopener noreferrer" target="_blank" class="">nearly 20% by 2030</a>.<a href="https://www.bruegel.org/working-paper/artificial-intelligence-adoption-public-sector-case-study" rel="noopener noreferrer" target="_blank" class="">A Bruegel case study of AI adoption in the public sector</a> reinforces this governance lesson. Successful adoption depended on early worker and end-user involvement, alignment across HR, IT, and business processes, and targeted subsidy support. But simply making AI available was not enough: legacy IT systems and slow process adaptation limited usage, showing that responsible adoption requires organizational change as much as technological investment.At a time when AI is already reshaping work globally, Bruegel’s research offers a set of guiding principles: connect innovation with inclusion, invest in skill-building, protect job quality, strengthen worker voice, and make mobility easier. The question is no longer whether AI will transform work, but whether institutions, employers, and workers will shape that transformation deliberately – in ways that expand opportunity, improve job quality, and ensure the future of work is inclusive by design.

In 2020, before the recent acceleration in generative AI adoption, the Center launched a research partnership with leading European think tank Bruegel to study the future of work, AI, and the broader impact of technology and digitalization. The context has changed significantly since then, but the questions at the heart of that research remain deeply relevant today.

Bruegel is a European think tank that specializes in economics. Established in 2005, it is independent and non-doctrinal. Bruegel’s mission is to improve the quality of economic policy with open and fact-based research, analysis and debate.It is committed to impartiality, openness and excellence. Bruegel’s membership includes EU Member State governments, international corporations and institutions.

Bruegel

Bruegel is a European think tank that specializes in economics. Established in 2005, it is independent and non-doctrinal.

AI and the future of work: Five lessons from Europe