According to the International Labor Organization (ILO), the global youth employment challenge remains stark. One in eight young people around the world are unemployed, while one in five are not in employment, education, or training (NEET).
At the same time, artificial intelligence (AI) is reshaping the world of work, with its impact increasingly visible at the entry level. The World Economic Forum reports that 37% of young workers globally are employed in occupations with medium to high exposure to AI-driven task change. This does not mean that 37% of young workers will lose their jobs. Exposure to AI reflects the potential for tasks within occupations to change through automation, augmentation, or both.
This distinction matters. AI may automate some routine tasks, but occupations are rarely made up entirely of routine tasks. As technology takes over portions of existing jobs, the value of skills such as problem-solving, communication, collaboration, adaptability, and judgment can increase. The ILO’s 2026 youth employment report similarly calls for greater investment in technical skills combined with social and cognitive capabilities, alongside stronger lifelong learning systems.
This creates a paradox. The technology contributing to rapid changes in the labor market can also become part of the response. Instead of asking only whether AI will replace jobs, a more useful question is: Can AI help people acquire the skills they need to remain productive as jobs change?
There is growing evidence that it can.
One important advantage of AI is personalized learning. Traditional classrooms often require learners with different abilities to follow the same curriculum and pace. AI-supported systems can instead identify where a learner is struggling and adapt learning content accordingly. Mindspark, an AI-supported adaptive learning platform in India, does this by assessing a student’s actual learning level and providing exercises targeted to specific gaps. A randomized evaluation found that students using Mindspark alongside regular classroom teaching made more than twice as much progress in mathematics as students in standard classrooms over approximately four months.
AI can also help make informal skills visible. Millions of young people develop capabilities through informal work, apprenticeships, family businesses, agriculture, and community activities, but these skills are often difficult to translate into formal qualifications. SkillLab, an Amsterdam-based technology provider working across 40 countries, uses AI to interview users about their work experience, identify their skills, and map them against the international standard labor framework. SkillLab’s platform covers more than 13,000 skills and supports 27 languages.
Kabakoo Academies in West Africa offers another innovative model. In their platform, upskilling happens through community and mobile-based learning, including WhatsApp. Its approach combines peer-supported learning with a multilingual AI mentor that helps young people develop practical skills for entrepreneurship and employment. The model also allows young people to use AI for tasks such as market research, business planning, and problem-solving.
These examples point toward a different model of workforce development. Instead of giving every young person the same training, AI can help assess what they already know, identify gaps against specific occupations, personalize learning, provide continuous practice and feedback, and connect skills to real market opportunities.
This last link is critical. Better learning alone does not guarantee better employment outcomes. The skills young people acquire must also reflect what employers need. For this reason, AI-enabled workforce development needs to connect learning with the demand side of the labor market. Learning providers should engage employers to define the occupational skills that training should target, while AI can translate these requirements into personalized learning pathways and assess learners’ progress against them.
The upskilling opportunities created by AI could be a game-changer for young people in underserved communities. A young person in a rural or climate-vulnerable area may have limited access to universities, training centers, career counselors, and professional networks. AI cannot solve infrastructure or labor-market constraints by itself. With the widespread availability of digital technologies, AI can reduce the cost of providing personalized learning and career support at scale. When these systems are linked to local employers, they can help young people move from learning to demonstrating relevant skills and, ultimately, accessing real work opportunities.
Therefore, to address the youth employment challenge in the age of AI, the priority should move beyond teaching young people how to use AI tools. The focus should be on enhancing employability by combining AI with the occupational and human skills that employers and markets value. This means creating skills systems that continuously connect what young people can do, what they need to learn, and what employers actually need.
References
- International Labour Organization. (2026). Global employment trends for youth 2026: Back to the future. International Labour Organization. https://www.ilo.org/publications/major-publications/global-employment-trends-youth-2026
- Muralidharan, K., Singh, A., & Ganimian, A. J. (2019). Disrupting education? Experimental evidence on technology-aided instruction in India. American Economic Review, 109(4), 1426–1460. https://doi.org/10.1257/aer.20171112 Cited by: 798
- SkillLab. (2023). AI-driven skill profiling and ESCO taxonomy integration. SkillLab B.V. https://skilllab.io/
- World Economic Forum. (2025). The future of jobs report 2025. World Economic Forum. https://www.weforum.org/publications/the-future-of-jobs-report-2025/
- International Labour Organization. (2026). Global employment trends for youth 2026: Back to the future. International Labour Organization. https://www.ilo.org/publications/major-publications/global-employment-trends-youth-2026
- World Economic Forum. (2025). The future of jobs report 2025. World Economic Forum. https://www.weforum.org/publications/the-future-of-jobs-report-2025/
- Muralidharan, K., Singh, A., & Ganimian, A. J. (2019). Disrupting education? Experimental evidence on technology-aided instruction in India. American Economic Review, 109(4), 1426–1460. https://doi.org/10.1257/aer.20171112