Brussels, 2 April 2025 – “Expanding real-time skills intelligence to accelerate Europe’s skills revolution”, an event organised by Cedefop, was held at the EESC Building in cooperation with Eurostat. EfVET participated in the high-level policy event gathering insights on skills intelligence for and from the VET ecosystem.
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Download the full event report
Alternative link: CEDEFOP REPORT
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The second day of events featured a session where Cedefop explored the future of labour market intelligence, highlighting the innovative use of web data to shape the next generation of labour market and skills analysis.
The skills revolution Europe needs is based on skills intelligence, cleansed and analysed data on labour market trends, and the skills needed within industries. Such intelligence can support data-driven decision-making, which is essential for policymakers and educators to align skills development with industry needs, support competitiveness and integrate/enhance skills for the dual digital/green transition.
This session explored how skills information based on online sources can be used to provide the labour market and the VET ecosystem with guidance policies. Best practices and methodologies for extracting meaningful information from online job advertisements (OJAs) were also discussed.
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In web skills intelligence, there is “no crystal ball”. Time, resources, and qualifications are needed for long-term investment. Merging conventional intelligence with skills intelligence powered by big data is the way forward.
However, the EU still has large gaps in basic #digital #skills – 90 million citizens still need to be upgraded – which are still far from being tackled. #Data intelligence (statistical expertise, analysis of raw data) should be central to #policy makers and civil society for the enhancement and proper implementation of the policies. The quality of #statistics and data coverage are therefore essential.
The data must be ‘cleansed’ by human scientific analysis by experts who consider a process of web data exploration, content collection, pre-analysis, raw data cleaning and final distillation. The involvement of #AI for statistical purposes could lead to a potential improvement of the algorithm to facilitate the process, and generative AI could be used to provide information. But there is still a long way to go in implementing AI in the workplace, and the EU needs to consider ethical and control factors on the use of data.
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The report was created by the EfVET team: Editorial and Photos by Michele Pasquale, Comms Manager. Revision by Paolo Nardi, Executive Director. Graphics/event notes by Jaime Rivas Larrauri, Comms trainee.
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