WP121 Web · Page 38

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  ILO Working Paper 121
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X Final discussion 
This study examines the exposure to GenAI within the labour markets of the LAC region, reveal­
ing both widespread potential impacts and significant variability across different demographics 
and sectors. Our findings indicate that a substantial proportion – between 30 and 40 percent 
of employment in LAC – is exposed in some way to GenAI. This exposure is linked with the eco­
nomic status of countries, suggesting that income levels are a strong correlate of GenAI’s impact 
on labour markets. However, it is crucial to note that such exposure does not imply automation, 
and that for the vast majority of these jobs, the potential lies in transforming the tasks that these 
occupations perform. Our estimates for the potential effects of automation in LAC amount to 2 
to 5 percent of employment depending on the country. These figures, while seemingly modest, 
should not be trivialized as they represent individuals’ livelihoods that are at stake. In addition, 
some of the jobs from the large category of “the big unknown” might move closer to automation 
over time, as the technology and its applications to workplace tasks develop further.
Comparisons of our results to other studies are complicated, due to the significant differences 
in the concepts applied, occasional lack of detailed data that would enable a more precise as­
sessment, diverging methods of presenting the findings, and the general scarcity of studies that 
cover non-HIC countries (Comunale and Manera, 2024). For example, Eloundou et al. (2023) state 
that up to 80% of the US workforce could have at least 10% of their tasks replaced, while 19% of 
workers could lose at least 50% of their tasks to LLMs – a finding that is hard to directly relate to 
our framework, except for the similarity of a much stronger augmentation effect over automa­
tion. McKinsey (2023) points to a similar group of “knowledge work” as being most exposed but 
focus the analytical work on additional value generation through productivity increases, rather 
than on direct effects on employment. WEF Future of Jobs (2023), even though global in scope, 
focuses exclusively on large enterprises, pointing to clerical and administrative jobs among oc­
cupations with the fastest expected declines. Goldman Sachs (2023), based on extrapolation of 
O*NET occupations to emerging economies, suggests that “most jobs and industries are only 
partially exposed to automation and are thus more likely to be complemented rather than substi­
tuted by AI”.38 According to our best knowledge, there are no prior studies with detailed insights 
to GenAI exposure in the LAC region and our estimates of total potential exposure are generally 
lower than the 40 percent estimated by Cazzaniga et al. (2024) for emerging economies. However, 
wealthier LAC countries show exposure levels closer to this estimate. 
Within this context, irrespective of country-specific differences, our estimations show that certain 
characteristics consistently correlate with higher GenAI exposure. Specifically, urban-based jobs 
that require higher education, are situated in the formal sector, and are held by individuals with 
higher relative incomes are more likely to come into interaction with this technology. Moreover, 
there is a pronounced tilt towards younger workers facing greater exposure, including the risk of 
job automation, in particular in the finance, insurance, and public administration sectors.