Globalisation, technological progress, and demographic change are having a profound impact on the world of work. These mega-trends are affecting the number and quality of available jobs, how they are carried out and the skills that workers will need in the future to succeed in an increasingly competitive landscape.
On average across the OECD countries covered by the Skills for Jobs database, more than five out of ten jobs that are hard-to-fill (“in shortage”) are found in high-skilled occupations (Figure 5.7). These jobs range from managerial positions to highly skilled professionals in the healthcare, teaching or ICT sectors. A relatively large share of occupational shortage (approximately 41% of total jobs that are hard-to-fill across the OECD) is also found in medium-skilled occupations, such as personal service workers or electrical and electronic trades workers. Fewer than one out of ten jobs in shortage across the OECD are found, instead, in low-skilled occupations. The intensity of occupational shortages, however, varies significantly across OECD countries. In Belgium and Estonia, more than nine out of ten jobs in shortage are of the “high-skilled” type. In Mexico, the demand for highly skilled professionals is significantly lower, with less than one out of ten jobs in shortage being “high-skilled” and the majority of jobs in shortage being found, instead, in “medium” to “low-skilled” occupations.
On average across 14 countries for which data are available, the share of online vacancies demanding Artificial Intelligence (AI) skills was very small and highest in the United States at 0.84% in 2022. However, the share of AI-related online vacancies grew by 33% between 2019 and 2022 on average across countries – with only Austria and Sweden not reporting growth over this period (Figure 5.8). The demand for AI-related jobs is highly concentrated, and often concerns positions in Information and Communication Technology (ICT) and Professional Services, with most sought after skills being related to Machine Learning – the systematic application of algorithms to synthesize the underlying relationships among data and information.
In most OECD countries, women participate more in education and training programmes than men in the 4 weeks prior to being interviewed (Figure 5.9). On average across OECD countries, women are 3.5 percentage points more likely to participate in adult learning. In Sweden and Iceland, the gap exceeds 10 percentage points in favour of women. The Slovak Republic and Türkiye are the only two countries in which men participated more than women in education and training. While there are significant benefits in terms of wages and employability in participating in educational and training programmes for both men and women, research has found that women who participate in job-related training earn higher wages than their male counterparts.
