利用人工智能发展职业教育与培训

Developing Vocational EducationandTraining with ArtificialIntelligence OECD Reviews of Vocational Education and Training Developing VocationalEducation and Training withArtificial Intelligence This work is issued under the responsibility of the Secretary-General of the OECD, and does not necessarily reflect theofficial views of OECD Member countries. This document was produced with the financial assistance of the European Union. The views expressed herein can inno way be taken to reflect the official opinion of the European Union. This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty overany territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. Please cite this publication as: OECD (2026),Developing Vocational Education and Training with Artificial Intelligence, OECD Reviews of Vocational Educationand Training, OECD Publishing, Paris, https://doi.org/10.1787/e9f76b4e-en. ISBN 978-92-64-91370-7 (print)ISBN 978-92-64-48249-4 (PDF)ISBN 978-92-64-76556-6 (HTML) OECD Reviews of Vocational Education and TrainingISSN 2077-7728 (print)ISSN 2077-7736 (online) Photo credits:Cover © WUT.ANUNAI/Shutterstock.com. Attribution 4.0 International (CC BY 4.0) This work is made available under the Creative Commons Attribution 4.0 International licence. By using this work, you accept to be bound by the terms of this licence(https://creativecommons.org/licenses/by/4.0/).Attribution– you must cite the work.Translations– you must cite the original work, identify changes to the original and add the following text:In the event of any discrepancy between the original work and thetranslation, only the text of the original work should be considered valid.Adaptations– you must cite the original work and add the following text:This is an adaptation of an original work by the OECD. The opinions expressed and arguments employed inthis adaptation should not be reported as representing the official views of the OECD or of its Member countries.Third-party material– the licence does not apply to third-party material in the work. If using such material, you are responsible for obtaining permission from the third party and forany claims of infringement.You must not use the OECD logo, visual identity or cover image without express permission or suggest the OECD endorses your use of the work.Any dispute arising under this licence shall be settled by arbitration in accordance with the Permanent Court of Arbitration (PCA) Arbitration Rules 2012. The seat of arbitration shallbe Paris (France). The number of arbitrators shall be one. Foreword Vocational education and training (VET) plays a central role in equipping people with the skills needed forwork, supporting productivity, inclusion and economic resilience. At the heart of VET systems lie curriculaand qualifications. They translate labour market demand into structured learning outcomes, recognisedcredentialsand training opportunities.Yet the processes through which these VET curricula andqualifications are developed remain largely invisible to learners and the public, despite being critical to therelevance, attractiveness and adaptability of VET systems. These development processes are under growing pressure, with rapid labour market change, while thevolume and complexity of curricula and qualifications continue to expand–partly reflecting trends towardsmodularisation and more tailored provision. Although VET development processes are typically rigorous,collaborative and grounded in stakeholder dialogue, they are also resource‑intensive and can struggle tokeep pace with fast‑moving change. In this context, AI has emerged as a potential tool to supportandimprove these processes. AIentered education and labour markets quickly,often before VET stakeholders had a sharedunderstanding of what it can do, how it should be used, or how it should be governed. In VET developmentin particular, adoption remains cautious: stakeholders recognise AI’s potentials, but it also raises criticalconcerns. This OECD work,Developing VET with AI provides an evidence-based and stakeholder-consulted snapshot in this area, drawing on OECD surveys of over290 stakeholders across 25countries,ten country case studiesidentifying thirty-oneconcrete AI use cases (published in a separate report), andstakeholder dialogue across 80stakeholders via interviews or workshops. The analysis shows that AI usein VET development is already being applied across key stages of VET development, from skillsanticipation and consultation to drafting, validation and alignment. At the same time, the evidence confirmsthat AI is not a shortcut: the core foundations of VET development continue to underpin VET systems, andbecome even more critical when AI is used. The challenge is thus not whether to use AI, but how tointegrate it transparently, securely and effectively within existing VET development processes.