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Other literature type . 2026
License: CC BY
Data sources: ZENODO
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Other literature type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
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Artificial Intelligence in Youth Work: Policy Lessons and Strategic Directions from the AI4YouthWork Project

Authors: AI4YouthWork Consortium;

Artificial Intelligence in Youth Work: Policy Lessons and Strategic Directions from the AI4YouthWork Project

Abstract

This publication presents the Policy Paper “Artificial Intelligence in Youth Work: Policy Lessons and Strategic Directions from the AI4YouthWork Project”, developed in the framework of the Artificial Intelligence for Youth Work (AI4YouthWork) project, a Cooperation Partnership in the Youth field co-funded by the Erasmus+ Programme of the European Union. The paper translates empirical evidence generated through the AI4YouthWork project into actionable policy recommendations for the ethical, inclusive, and sustainable integration of Artificial Intelligence (AI) into youth work systems across Europe. It addresses a significant structural gap: while AI governance and digital transformation strategies are increasingly central to European policymaking, youth work remains largely absent from these frameworks. The document is grounded in a transnational research process, including: A systematic literature review of 145 international and European sources (48 selected for in-depth analysis); Focus groups with 72 youth work professionals across several European countries; Expert interviews in AI, youth work, and digital education; A validation survey involving 100 youth workers, organisations, training providers, and policy stakeholders; Piloting of training resources, including a multilingual Digital Catalogue of 48 Open Educational Resources and an AI Training Toolkit. The paper identifies structural challenges currently affecting youth work in relation to AI, including fragmented competence development, ethical and legal uncertainty, unequal access to training, and the risk of marginalising youth work in digitally mediated environments. Based on this evidence, the policy paper proposes coordinated, multi-level action across European, national, and regional governance systems. The recommendations are organised into seven key areas: Inclusive Training Opportunities Lifelong Learning and Continuous Professional Development Ethical and Trustworthy AI in Youth Work Sustainable Funding and Resource Development Cross-Sector Cooperation and Knowledge Exchange Scaling and Sustainability Strengthening Collaboration Networks and Communities of Practice The publication argues that AI competences for youth workers should be recognised as a matter of public interest and embedded into qualification systems, professional standards and youth strategies, emphasising how AI integration can reinforce core youth work values and functions.

This publication is a deliverable of the project entitled “Artificial Intelligence for Youth Work”, a Cooperation Partnership in the Youth field co-funded by the Erasmus+ Programme of the European Union under Grant Agreement No. 2023-2-IT03-KA220-YOU-000170929. The views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the granting authority. Neither the European Union nor the granting authority can be held responsible for them.

Keywords

Youth, Policy, AI Competence, Youth work, AI Education, AI Skills, artificial intelligence

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green