What is the possible effect of generative AI on employment?

To assess the potential impact on existing employment from generative AI, we apply the scores of occupational exposure to generative AI to labour force survey data for more than 140 countries. This allows us to derive both global estimates and estimates among countries in different income brackets.

With respect to automation, the share of employment that is exposed is highest in high-income countries, reflecting their greater economic and labour market diversification. In low- income countries, the share of employment potentially exposed to automation is much smaller, due to the greater share of workers employed in occupations that would not be exposed to generative AI technology such as in agriculture, transport or food vending. 

A larger share of jobs falling into the augmentation category suggests that, at least in the near future, generative AI systems similar to GPT are more likely to become productivity tools, supporting and speeding up the execution of some tasks within certain occupations. 

The digital divide will, nonetheless, influence how the benefits of such productivity tools are distributed among societies and countries, with high-income countries and privileged groups likely to reap the biggest rewards. Low-income countries, in particular, are at risk of falling behind. While up to 10.4 per cent of employment in these countries is found in the potential augmentation category, in practice potential benefits of GenAI technologies are likely to be limited, as the lack of reliable infrastructure will constrain their application.

NOTE: “The Big Unknown” refers to those professions that are at the junction of automation and augmentation, meaning they could either be transformed through GenAI-enabled augmentation or suffer displacement through automated substitution.