US vs Venezuela: AI Job Risk and Economic Collapse

Same peak score, completely different contexts

The 8.5/10 clerical exposure score that appears for both the United States and Venezuela reflects the same underlying reality: administrative and data-processing tasks - scheduling, record-keeping, document processing, data entry - fall squarely within current AI capability. The score is occupational, not national. A data entry clerk in Caracas has the same task susceptibility as one in Chicago.

What differs is everything else. The US has $90,026 in GDP per capita (World Bank Open Data, CC BY 4.0, 2025), a functioning enterprise software market, access to every major commercial AI platform, and employers with demonstrated willingness to invest in AI-driven back-office automation. Venezuela, at $3,495 per capita (World Bank Open Data, 2025), has undergone one of the most severe economic contractions in modern Latin American history. Power outages are routine in major cities. Internet infrastructure is degraded. Enterprise software procurement is functionally impossible for most employers.

The US Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) May 2025 release (2024 data year), accessed via ILO ILOSTAT (CC BY 4.0), covers 143,066,500 American workers. Venezuela's ILO ILOSTAT (CC BY 4.0) 2013 data covers 12,948,000 workers - a figure that almost certainly overstates the current workforce given mass emigration and economic contraction since that year.

Side-by-side: occupation groups in both countries

The table below compares both countries across available ISCO-08 occupation categories. US data is BLS OEWS May 2025, accessed via ILO ILOSTAT (CC BY 4.0). Venezuela data is ILO ILOSTAT (CC BY 4.0), 2013 data year. Venezuela's dataset does not include separate Technicians and associate professionals or Elementary occupations categories at the ISCO-1 level for this data year. Venezuela wage data is not available in the ILO ILOSTAT series for this year.

Venezuela's workforce structure is dominated by service and sales (36.9%) and craft and trades (20.0%) - both scoring at 3.5/10 or below. Together those two groups represent 57% of tracked employment in the 2013 data. This is not inherently a sign of low vulnerability - it reflects an economy built around informal commerce, physical trades, and resource extraction rather than knowledge-work and administration.

Why Venezuela's average is lower despite the same peak

Venezuela's 4.09/10 average versus the US at 5.07/10 is explained almost entirely by the service and sales concentration. Of Venezuela's 12.9 million tracked workers in 2013, 4.77 million - more than a third - work in service and sales roles scoring 3.5/10. The US service and sales group is also large (30.27 million, 21.2% of workforce), but the US has far more workers in higher-scoring categories: 35.74 million professionals (6.5/10), 23.2 million managers (5.5/10), and 22.9 million clerical workers (8.5/10).

Venezuela's craft and trades sector (2.6 million workers, 20.0% of workforce, score 2.5/10) is the second-largest group. Physical work in construction, repair, and skilled manufacturing resists automation in any economy - and even more so in one where advanced robotics remain economically out of reach. Venezuela's agricultural sector (937,800 workers, 7.2%, score 3.0/10) also contributes to the lower average.

Venezuela's 2013 data does not show separate Technicians and associate professionals or Elementary occupations categories at ISCO-1 level - groups that appear in the US and most other country datasets. This limits direct comparability at the margin but does not materially change the overall picture.

The economic collapse: what happened after 2013

Any analysis of Venezuela's AI risk must be set against the collapse that followed 2013. Venezuela's GDP per capita was approximately $3,495 in 2025 (World Bank Open Data, CC BY 4.0). IMF estimates put the cumulative GDP contraction at roughly 80% between 2014 and 2021 - one of the deepest peacetime economic collapses on record globally. Hyperinflation reached approximately 1,000,000% in 2018 before the government introduced currency redenomination (IMF World Economic Outlook data).

The collapse gutted institutional capacity across both private and public sectors. Many private-sector employers in the categories captured by the 2013 data - professional services, manufacturing, commerce - have shrunk dramatically or ceased to operate. The state oil company PDVSA, once a dominant employer, saw production fall from roughly 2.4 million barrels per day in 2015 to under 800,000 by 2020 (OPEC data). The 2013 occupational data reflects a pre-collapse economy that no longer exists in the same form.

Venezuela's unemployment rate of 5.31% (World Bank Open Data, 2025) appears low, but in a collapsed economy this figure reflects the prevalence of informal subsistence work rather than a healthy labour market. When formal employers disappear, workers shift to informal trade and survival-oriented activities that formal labour statistics cannot fully capture.

The emigration factor: 7.7 million workers carrying AI exposure abroad

The UNHCR and International Organization for Migration (IOM) estimate that approximately 7.7 million Venezuelans had left the country by 2024 - the largest displacement crisis in Latin American history. Destinations include Colombia (over 2.9 million), Peru, Ecuador, Chile, Brazil, and the United States.

This emigration skews toward working-age adults with secondary and tertiary education - precisely the professionals, technicians, and clerical workers who score highest on AI exposure and who were most likely to have formal sector employment in Venezuela's pre-collapse economy. UNHCR profiling data from major destination countries supports this pattern.

In other words, Venezuela's most AI-exposed workers have largely left Venezuela. They are now working in countries - particularly Colombia, Peru, and Chile - where AI deployment timelines are much shorter. Venezuela's domestic workforce, reduced in size and shifted toward informal and agricultural work, has lower average AI exposure than the 2013 data suggests. The emigrants who carried the high-exposure clerical and professional skills have effectively exported Venezuela's AI risk to other Latin American labour markets.

Economy context: US vs Venezuela

The table below uses World Bank Open Data (CC BY 4.0, 2025) and UNDP Human Development Report 2025 (HDR 2025, 2023 data year, licence CC BY 3.0 IGO).

The safest jobs from AI in both countries

Venezuela's craft and related trades workers (2,595,300 workers, score 2.5/10) represent 20% of the 2013 tracked workforce and are the most AI-insulated group in the data. Construction, repair, and skilled manual trades require physical dexterity in variable environments that AI systems cannot replicate cost-effectively - in any economy, let alone one without the capital to deploy advanced robotics.

What this means for workers in both countries

For US workers, particularly the 22.9 million clerical workers at 8.5/10 and 35.74 million professionals at 6.5/10, AI adoption is already a present-tense reality. Enterprise AI tools are deployed in financial services, insurance, healthcare administration, and legal support. The full US analysis documents which specific groups face 1-3 year displacement timelines. Workers in these categories who are building AI-adjacent skills are materially better positioned than those who are not.

For Venezuelan workers still in Venezuela, the AI risk question is secondary to far more immediate economic pressures. Inflation, access to basic goods, power supply reliability, and the functioning of the financial system are more pressing than whether their job tasks fall within AI capability. Venezuela's risk velocity of 0.5 reflects the structural reality that even if AI tools were freely available and affordable, the enterprise capacity to deploy them has largely ceased to exist.

The more consequential AI risk story for Venezuelans concerns those who have emigrated. Venezuelan professionals, clerical workers, and technicians now living in Colombia, Peru, Chile, and the United States are in countries where AI deployment is accelerating. Their AI exposure - carried from a pre-collapse Venezuelan economy - is now being realized in entirely different national contexts. The 2013 ILO data cannot capture this diaspora dynamic, but it is the most relevant AI risk question for the Venezuelan workforce as a whole.