AI and Jobs: Which Workers Face the Biggest Changes?

What happened?

The biggest labour-market question is no longer simply whether AI will replace jobs. It is how quickly tasks will change, who benefits and who gets support to adapt. An ILO-World Bank study examined generative-AI exposure across 135 countries and found that developing economies may face disruption before realizing productivity gains.

Key points

• An ILO-World Bank study examined generative-AI exposure across 135 countries and found that developing economies may face disruption before realizing productivity gains.
• ILO research says women are disproportionately exposed to GenAI because women are concentrated in more exposed occupations and remain underrepresented in many AI-related fields.
• The ILO's 2026 employment report warns that AI adoption, trade uncertainty and weak investment are complicating improvements in decent work.
• Recent research using job-vacancy data finds AI-related skills remain concentrated in a relatively technical core of the labour market.
• Exposure to AI is not the same as job loss; many occupations are more likely to be transformed than eliminated.

What we know

1. An ILO-World Bank study examined generative-AI exposure across 135 countries and found that developing economies may face disruption before realizing productivity gains.
2. ILO research says women are disproportionately exposed to GenAI because women are concentrated in more exposed occupations and remain underrepresented in many AI-related fields.
3. The ILO's 2026 employment report warns that AI adoption, trade uncertainty and weak investment are complicating improvements in decent work.
4. Recent research using job-vacancy data finds AI-related skills remain concentrated in a relatively technical core of the labour market.
5. Exposure to AI is not the same as job loss; many occupations are more likely to be transformed than eliminated.

What officials/people involved say

The ILO repeatedly emphasizes that AI changes tasks and job quality as well as employment numbers. The World Bank contribution highlights digital infrastructure and differences in how work is organized across economies.

Background

A job is a bundle of tasks. AI can automate some tasks while leaving others—especially those requiring judgment, relationships, physical presence or accountability—to people. That is why two workers with the same job title can face very different effects.

Why it matters

Workers should pay attention to the tasks they perform rather than panic about job titles. Skills such as data literacy, communication, problem-solving, domain expertise and the ability to supervise technology can become more valuable as routine tasks are automated.

What happens next?

Governments and employers will need training systems that are faster and more practical. Individuals can start by learning how AI tools work, where they fail and how to combine them with real professional expertise. The goal is not to compete with every machine, but to become good at work where humans and machines complement each other.