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ISLAMABAD: A joint study released by the International Labour Organisation (ILO) and the World Bank on Friday has stated that generative artificial intelligence (GenAI) is set to reshape labour markets worldwide, but with uneven impacts across countries.
The background study for the forthcoming World Development Report 2026 examined labour market exposure to GenAI across 135 countries, covering around two-thirds of global employment.
It showed that differences in digital infrastructure and job task composition are key in shaping how risks and opportunities are distributed between advanced and developing economies.
It said that in developing economies, disruption may materialise faster than productivity gains due to existing digital gaps and differences in how work is performed.
The study identified a “small buffer, big bottlenecks” dynamic in developing countries. Workers in jobs facing automation exposure are often already connected and, therefore, may experience displacement pressures relatively quickly. Workers in jobs with augmentation potential frequently lack reliable internet access, limiting their ability to realise productivity gains.
In low- and lower-middle-income countries, the share of jobs exposed to automation is smaller overall. However, these jobs often represent formal, higher-quality service sector roles — occupations disproportionately held by women and younger workers — and entry-level clerical and administrative positions that historically served as pathways into decent work.
This raises the risk of a “white-collar bypass”, where office-based jobs that supported upward mobility and women’s labour force participation in advanced economies may not fully materialise in today’s developing countries, the study said.
Exposure to GenAI is higher in advanced economies, particularly in clerical and professional occupations. Developing countries, while less exposed overall, face structural constraints that limit their ability to benefit from the technology.
The study found that exposure to GenAI is higher in advanced economies. Around 30 to 32 per cent of employment in high-income countries is exposed, while in low-income countries, this figure is close to 1 to 15pc.
A key finding is the role of the digital divide. Workers in jobs vulnerable to automation are often already online, even in low-income settings, meaning job losses could happen relatively quickly.
These jobs often represent relatively higher-quality jobs in lower-income countries, including clerical and administrative positions that have historically offered a pathway to decent work, particularly for women and young workers. The concern is that AI-driven automation could close off these pathways.
At the same time, many workers in roles with potential for productivity gains lack reliable internet access in lower-income settings, limiting their ability to benefit from GenAI. In addition, while occupations may share similar titles across countries, the tasks performed in the same job differ significantly depending on the location.
The study showed that workers in lower-income economies tend to perform fewer non-routine analytical tasks, rely less on computers at work and have more routine or manual work, reducing the scope for productivity gains from GenAI implementation.
Overall, the research finds that GenAI’s labour market impact will depend not only on technological capability, but also on digital infrastructure, task organisation and skills.
The paper pointed to the need for policies that expand digital connectivity, support skills development, and strengthen labour market institutions and social protection systems to ensure that the benefits of GenAI are more widely shared.
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