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Digital Education Action Plan - Action 10 Artificial intelligence and analytics

Predicting future skills with data


What skills will be needed on the labour market in the coming years? How can we make the best use of the data available online to capture insights and improve decision-making in education?

Under this action, artificial intelligence and analytics pilot projects will be launched to predict future skills and skills shortages.

Various data sources will be combined, compared and analysed with artificial intelligence techniques to build predictive models for future skills.

The action will also provide insights on what educational policies are required to address gender balance and inclusion within certain sectors.


Information available online, such as vacancy notices and employment statistics, could provide valuable insights for education policy but data are rarely used in a comparative way.

As skills gaps emerge, better data analysis, using machine learning, artificial intelligence and learning analytics, could allow Member States to adapt and respond to skills needs and trends.

Pilot projects in these fields could help identify a model to predict skills shortages for the future and support education systems to develop targeted educational offers.


The Commission will pilot data analytics projects to predict the learning journeys and training requirements for future competence profiles.

The commission has taken action to make optimal use of artificial intelligence through investments in research and innovation under the Horizon 2020 Framework Programme and the creation of a Digital Single Market. Measures include a comprehensive framework for the free flow of personal and non-personal data, first-class connectivity across Europe and stronger cybersecurity rules. The Commission will build further on this progress with an integrated approach to strengthen Europe’s competitiveness in artificial intelligence as well as to provide a stable regulatory framework to address citizens’ concerns about the legal, ethical and socio-economic implications of artificial intelligence use.


  • 2018: identify digital tools and experts
  • 2019: build a common data repository which centralises different data sets and develop and test a set of algorithms that match future competency levels to learning activities.
  • 2020: build a repository of learning activities and learning elements for the skill profiles that were used in the pilot projects.