Future of Jobs Report 2025 &
Global Skills Taxonomy

The 'Future of Jobs Report 2025' is clearly structured into chapters: Executive Summary (pp. 6–10), Drivers of Transformation (pp. 11–17), Skills Outlook (pp. 18–33), sectoral analyses (pp. 34–51), Measures & Stakeholders (pp. 52–65). The 'Global Skills Taxonomy' (pp. 3–10 in the Toolkit) is well organized into 9 main categories. Charts like “Top 10 Skills” (Fig. 3.1, p. 21) and “Skills Taxonomy Map” (Toolkit p. 6) help visualize the content clearly.

Skills are systematically classified (e.g. cognitive, self-efficacy, working with others – Toolkit pp. 6–9). The report highlights priorities for training and reskilling (pp. 28–30), but lacks concrete instructional formats or skill levels. The description remains high-level; no curricular implementation support or pedagogical measures are detailed. Skills are mostly listed as terms (e.g., p. 21, pp. 6–9 in Toolkit) without verbal definitions or contextualized explanations. Some training priorities...

The chapter 'Drivers of Labour-Market Transformation' (pp. 11–17) provides a comprehensive context: technological advances (e.g. generative AI), geopolitical tensions, energy transition, inflation. Supported by sectoral analyses and global comparison data. Contextualization is enhanced through Skills Demand Maps (pp. 22–27).

Diversity and inclusion are referenced in 'Social Jobs and Equity' (pp. 56–59). While social jobs and gender equity are discussed, a deeper ethical framing is missing. The taxonomy lacks explicit reference to values or attitudes—ethics is not integrated as a skill domain.

Topics like climate change, social inclusion, digital divide, and public-private partnerships are addressed (pp. 14, 56–60). While skills are linked to societal change, the focus remains on labor market integration and economic resilience, not transformative participation. The approach is primarily employability-oriented.

Chapters on Skills Transformation (pp. 18–33) and Job Disruption (pp. 11–17) clearly respond to future challenges. Terms like 'Resilience', 'AI Literacy', and 'Systems Thinking' reflect future-relevant skills. Scenario analyses of skill shifts and automation disruption are clearly presented. However, there's no explicit discussion of a desirable future.

Neither the report nor the toolkit explicitly mentions learning or educational theories. Education is presented functionally as skill development. Terms like 'competence', 'learning', or 'didactics' are absent; the approach remains economic-oriented.

Skills are grouped using the KSA model (Toolkit pp. 6–8): knowledge, skills, and attitudes. However, this logic is not explicitly justified or educationally framed. The categories are understandable but lack theoretical depth.

Chapter 'Methodology' (pp. 66–68) describes a survey design: 803 companies from 27 sectors were surveyed, plus qualitative expert interviews. The methodological approach is documented but lacks deeper theoretical-methodological grounding. The taxonomy is based on synthesis of global frameworks (Toolkit pp. 4–5).

Responsibility lies with companies, education providers, and multilateral organizations (pp. 60–65). Implementation is through reskilling programs, competence centers, and partnerships. Teachers and learners are hardly mentioned; educational context transfer is vague.

Goals like reskilling, economic growth, and resilience against disruption are clearly stated (pp. 6–9, 28–30). However, there's no educational policy vision or reference to overarching goals like ESD or social innovation.