JOBS OUTCOMES STORY                 RESULTS
                                              Analysis found that 30–40% of jobs in Latin America
                                              and the Caribbean are exposed in some way to gen-
Quantifying the                               erative artificial intelligence (Gen AI), with exposure
Jobs Potential of                             highly linked to a country’s economic status. Exposed
                                              jobs are more likely to be urban, formal, and high-
AI in Latin America                           er-paying, and to require higher education.

and the Caribbean                             Between 8 and 12% of jobs in the region could see a
                                              boost in productivity by harnessing Gen AI – but up
                                              to half, some 17 million jobs, won’t be able to lever-
                                              age the potential benefits because of a lack of digital
                                              infrastructure.
AT A GLANCE                                   Gen AI puts 2–5% of jobs in the region at risk of
REGION/COUNTRY Latin America                  automation, disproportionately impacting younger,
and the Caribbean                             educated, urban workers, and especially women. On
                                              average, women workers are twice as likely to be at
PROGRAM/PROJECT Publication:
                                              risk of automation from Gen AI.
Buffer or Bottleneck? Employment
Exposure to Generative AI and the             Between 13% and 22% of workers are exposed to Gen
Digital Divide in Latin America               AI in contexts that could lead either to automation
                                              or augmentation, depending on the evolution of this
                                              technology, workers’ characteristics, and comple-
                                              mentary policies.
THE CHALLENGE
Generative artificial intelligence (Gen AI) is set to potentially transform the labor market, presenting both op-
portunities and challenges. Studies about its possible impacts have generally focused on high-income coun-
tries. But AI might be a crucial path to greater productivity in emerging markets – or, like other recent waves
of technological change, it might widen the gap between low- and high-income workers. These effects are of
particular concern to Latin America and the Caribbean (LAC), one of the world’s most unequal regions, and
one that has struggled with a persistent productivity gap, in large part because of barriers to innovation and
technology adoption. To effectively minimize the risks and leverage the benefits of Gen AI, LAC countries would
need to understand their economy’s occupational exposure to the technology – yet that type of assessment
had never before been undertaken in the region.


WBG APPROACH
In partnership with the International Labor Organization, the World Bank produced the first analysis of the Latin
American labor market’s exposure to Gen AI and what it means for the hundreds of millions of workers across
the region. The policy paper leveraged a rich set of harmonized household and labor force surveys, breaking down
– by country, by demographic, and by sector – the jobs at risk of automation, those where AI could boost pro-
ductivity, and those that might fall in between. One major consideration for this kind of analysis is that develop-
ing economies tend to adopt technology more slowly, a variable that the report conscientiously accounted for.
Critically, all the data on the country level has been made publicly available online. This data is foundational to
country-specific insights, informing policy responses that can leverage AI to benefit workers, grow economies,
and increase prosperity for all.


LESSONS LEARNED
One of the analysis’s most urgent lessons is the need to equalize digital access in developing countries. Inade-
quate digital infrastructure prevents countries – especially lower-income countries – from capitalizing on Gen
AI, making it a major bottleneck for increasing productivity. Additionally, it is crucial to scale up the collection
of high-frequency labor market data in developing countries, to move from measuring Gen AI exposure to mea-
suring its impacts. Such data would allow the early detection of labor-displacement effects and inform evi-
dence-based labor market policies.


NEXT STEPS
A key step will be to support governments in creating policies that minimize Gen AI’s disruptions and maximize
its benefits: strengthening job protection measures and social protection systems, equipping workers with skills,
expanding digital infrastructure, and reducing the digital divide. Future work could also dig into the details and
data gaps that limited this analysis. This includes collecting better data on the use of technology at work, on the
characteristics of workers’ internet access, or on how the tasks of certain types of jobs vary across countries.
These methods will be updated and scaled up globally for the next World Development Report on AI.