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Brussels, |
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EU for Jobs: Predict the skills of the future
How the national Public Employment Services (PES) are using data and skills-based matching to respond to digital, demographic and green transitions. EU sollecita uno sforzo particolare per prepare gli Europei al mercato del lavoro.
Europe’s labour markets are entering a phase in which employment policy can no longer rely only on traditional job categories. Digital technologies, artificial intelligence, demographic pressures and the green transition are changing the skills required across sectors. Public Employment Services are therefore beginning to use data-driven tools, vacancy analysis and skills-based matching to anticipate future labour demand and design more responsive training policies.
By A. Durand, eEuropa
Brussels, 3 June 2026 - 6 MINUTES READ
Brussels, 3 June 2026 - 6 MINUTES READ
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Europe’s labour market is changing faster than many employment and training systems were designed to manage. Digitalisation, A.I., demographic change and the green transition are reshaping job requirements across almost every sector. The issue is no longer only whether new jobs will be created or old jobs will disappear. The deeper question is whether workers, employers and public institutions can identify the skills that will matter before shortages become structural.
This is why skills intelligence is becoming a strategic tool for employment policy. Traditional labour-market analysis has often focused on occupations, qualifications and sectors. These indicators remain useful, but they are increasingly insufficient. A job title may hide very different skill requirements, while the same skill can be relevant across several occupations. In this context, employment services need to understand not only where vacancies exist, but which competences are actually demanded by employers. The European Commission has highlighted the role of Public Employment Services in helping jobseekers and employers prepare for future skills needs, particularly through stronger data analysis, more responsive training programmes and skills-based approaches. The example of Luxembourg’s public employment service, ADEM (Agence pour le développement de l’emploi) , is particularly relevant. Its work shows how algorithms can be used to extract skills from open vacancies and feed labour-market intelligence into tools such as jobinsights.lu, which tracks trends across occupations and sectors. From occupation to skillsThe most important policy shift is the move from occupation-based matching to skills-based matching. Instead of simply connecting a person with a vacancy that carries a familiar job title, employment services can analyse what a jobseeker can actually do and compare it with the skills required by employers.
This can improve matching, but it can also reveal hidden opportunities. A worker whose previous occupation is declining may still possess transversal skills that are valuable in another sector. |
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This matters because the labour market is becoming more polarised and more fluid at the same time. Some technical specialisations may lose relevance, while others expand quickly. The Commission underlines that digitalisation, AI and wider economic shifts are affecting most occupations, with some IT specialisms shrinking while areas such as cybersecurity and data science are growing.
There is also a practical implication for training policy. If public authorities can identify skills demand from vacancy data, employer feedback and shortage occupation lists, they can adapt reskilling and upskilling programmes more quickly.
This is particularly important for workers exposed to technological change, older workers facing requalification needs, and companies struggling to recruit in fast-changing sectors.
However, there is a risk in treating skills forecasting as a purely technical exercise. Algorithms can identify patterns in vacancies, but they cannot fully capture the quality of jobs, the working conditions behind them, or the strategic choices that governments and firms make. A purely data-driven approach may also reinforce existing labour-market biases if it only reflects current employer demand. For this reason, quantitative labour-market intelligence must be combined with qualitative input from employers, counsellors, trade unions, training providers and local institutions.
The broader lesson for Europe is clear: skills policy is becoming part of economic resilience. Countries that can anticipate skills demand, support workers in transition and help employers recruit on the basis of real competences will be better placed to manage the digital and green transitions. Those that rely too heavily on outdated qualifications or rigid occupational categories may face deeper shortages, lower productivity and greater social exclusion.
For EU policymakers, the next step is to connect skills intelligence with wider policy instruments: employment services, vocational education, lifelong learning, industrial strategy and EU-level initiatives such as ESCO (European Skills, Competences, Qualifications and Occupations), Europass, EURES (EURopean Employment Services) and the Pact for Skills. The challenge is not simply to predict the future of work, but to build institutions capable of reacting before workers and firms are left behind.
This is particularly important for workers exposed to technological change, older workers facing requalification needs, and companies struggling to recruit in fast-changing sectors.
However, there is a risk in treating skills forecasting as a purely technical exercise. Algorithms can identify patterns in vacancies, but they cannot fully capture the quality of jobs, the working conditions behind them, or the strategic choices that governments and firms make. A purely data-driven approach may also reinforce existing labour-market biases if it only reflects current employer demand. For this reason, quantitative labour-market intelligence must be combined with qualitative input from employers, counsellors, trade unions, training providers and local institutions.
The broader lesson for Europe is clear: skills policy is becoming part of economic resilience. Countries that can anticipate skills demand, support workers in transition and help employers recruit on the basis of real competences will be better placed to manage the digital and green transitions. Those that rely too heavily on outdated qualifications or rigid occupational categories may face deeper shortages, lower productivity and greater social exclusion.
For EU policymakers, the next step is to connect skills intelligence with wider policy instruments: employment services, vocational education, lifelong learning, industrial strategy and EU-level initiatives such as ESCO (European Skills, Competences, Qualifications and Occupations), Europass, EURES (EURopean Employment Services) and the Pact for Skills. The challenge is not simply to predict the future of work, but to build institutions capable of reacting before workers and firms are left behind.
To understand what citizens expect from their working future, the EU and national authorities will also need to monitor people’s expectations continuously throughout their careers. Lifelong learning policies cannot be designed only around institutional priorities, technological forecasts or employer demand. They must also reflect the evolving aspirations, concerns and constraints of European citizens.
This means aligning EU and national learning strategies with the real demand emerging from society: the need for employability, career mobility, security, inclusion and meaningful participation in a changing labour market.
This means aligning EU and national learning strategies with the real demand emerging from society: the need for employability, career mobility, security, inclusion and meaningful participation in a changing labour market.
