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Title page 1

Contents 6

Foreword 4

Acknowledgements 5

Abbreviations and acronyms 8

Executive summary 10

1. Overview and key insights 13

In Brief 14

1.1. AI and the labour market relevance of VET development: Potential and challenges 14

1.2. Why this cross-country study is important 18

References 27

2. The potential of artificial intelligence in vocational education and training development 31

In Brief 32

2.1. Common practices in VET curriculum and qualification development 32

2.2. What tasks could AI help improve in VET development? 43

References 49

3. Leveraging AI for vocational education and training development: Current and emerging use cases 51

In Brief 52

3.1. Who uses AI to support VET development, and how? 52

3.2. In which tasks is AI used to support VET development? 56

3.3. For which types and subjects of VET programmes is AI used? 61

3.4. What data and AI tools are used or piloted for VET development? 63

References 66

4. Leveraging AI for vocational education and training development: Barriers and potential risks 68

In Brief 69

4.1. Barriers to effective, secure and inclusive AI use in supporting VET development 70

4.2. Potential risks associated with AI use in VET development 73

References 76

5. Policy considerations 77

In Brief 78

5.1. The uniqueness of VET development and the need of VET-specific AI principles 78

5.2. Policy considerations 79

5.3. Next steps 90

References 91

Tables 7

Table 1.1. Occupational standards, qualifications and curriculum in VET 22

Table 1.2. The scope of this study on VET development and its relevance within the full VET cycle 27

Table 2.1. Different approaches to structuring standards, qualifications and curricula in VET across countries 34

Table 2.2. Examples of the roles of stakeholders in VET development in selected countries 36

Table 2.3. Governance and legal frameworks of the development of VET curricula and qualifications in selected countries 40

Table 2.4. Examples of the scale of VET qualifications and curricula in selected countries 46

Table 3.1. Possible curriculum revision due to the integration of digital technologies and sustainability in VET and education-wide 61

Table 3.2. Examples of data resources or information used for AI-supported VET development in selected countries 64

Figures 7

Figure 2.1. VET development is a process of translating labour market needs into curricula 34

Figure 2.2. Primary sources for the development of VET curricula and qualifications 39

Figure 2.3. Conflicting stakeholder needs, interests and priorities in the process of VET development 45

Figure 2.4. Major challenges in VET development and main motivation for using AI 48

Figure 3.1. AI use varies across VET stakeholders, with public VET agencies and industry partners making greater use of AI than VET providers 53

Figure 3.2. Digital competences are integrated in the VET curriculum in many countries 62

Figure 3.3. What type of AI tools are used or piloted? 65

Figure 4.1. There are barriers that limit both the uptake and effective use of AI in VET development 70

Figure 4.2. Generational gaps in digital skills are wide in some countries 71

Boxes 19

Box 1.1. Examples of efforts to bring agility, precision, speed and efficiency to VET curriculum development in the European Union 19

Box 1.2. Definition and scope of VET curriculum and qualification development in this report 21

Box 1.3. Overview of ten case studies focussing on AI use cases in VET development 23

Box 2.1. European Software Skills Alliance and Digital Europe 43

Box 5.1. Examples of relevant AI guidelines 84

Box 5.2. Capacity building models that could be drawn for AI literacy and digital skills for VET development 87

Box 5.3. What enables and ensures secure use of AI in VET? 90

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