Key findings
- Clerical support workers score 8.5/10 on AI exposure - El Salvador's highest-risk group. 151,000 workers (5.2% of the workforce) in administrative, government, and BPO roles face the most immediate AI adoption pressure.
- Professionals score 6.5/10, covering 222,000 workers (7.7%). El Salvador's professional cohort includes lawyers, accountants, engineers, and a growing software development community serving US clients.
- Service and sales workers represent the largest group at 798,000 workers (27.6%), scoring 3.5/10 - below the displacement threshold for most near-term AI deployment scenarios.
- Elementary occupations score just 2.0/10 and cover 682,000 workers (23.6%) - largely in construction support, cleaning, street commerce, and domestic service. These roles depend on physical presence and manual judgment AI cannot replicate.
- El Salvador's weighted average of 3.56/10 reflects a workforce where informal commerce and remittance-funded consumption dominate over formal sector white-collar employment.
2.89 million workers, ILO ILOSTAT data
Employment data comes from ILO ILOSTAT (CC BY 4.0), based on DIGESTYC (Direccion General de Estadistica y Censos) El Salvador's Encuesta de Hogares de Propositos Multiples (EHPM). Classification follows ISCO-08 major group structure across El Salvador's 2.89 million employed workers.
El Salvador's economic structure creates a distinctive AI exposure profile. Remittances from the Salvadoran diaspora in the United States exceeded 24% of GDP in recent years - among the highest ratios in the world. This capital inflow supports household consumption and small commerce more than formal sector job creation, which keeps the workforce concentrated in service, craft, and elementary occupations with low AI exposure. The formal sector - concentrated in San Salvador's financial district and the country's industrial parks - is proportionally small but faces faster AI adoption through multinational technology transfer.
The most AI-exposed jobs in El Salvador
Clerical support workers score 8.5/10 and cover 151,000 workers - 5.2% of total employment. These workers are concentrated in San Salvador's banking sector (Banco Agricola, Banco Davivienda El Salvador, and Scotiabank El Salvador all have significant operations), government ministries, and a growing business process outsourcing industry. El Salvador has actively marketed itself as a nearshore BPO destination for US companies due to cultural proximity, US dollar currency, and time zone alignment. BPO workers handling data processing, insurance claims, and customer account management face the same AI displacement timeline as their counterparts in the Dominican Republic and Colombia: 3-5 years as US clients deploy AI automation.
El Salvador's Bitcoin legal tender status (adopted in 2021) has attracted a small but notable fintech and crypto services sector, bringing technology workers who encounter AI tools natively. This sector is too small to move aggregate exposure numbers but represents the fastest-moving frontier of AI adoption in the country.
Professionals at 6.5/10 cover 222,000 workers (7.7%). The professional class includes legal professionals, accountants, civil engineers working on infrastructure projects, and healthcare professionals. AI augmentation is already visible in legal document review (several Central American law firms use AI tools for due diligence on cross-border transactions) and in accounting through automated bookkeeping platforms.
| Occupation Group (ISCO-08) | AI Score | Robotics Risk | Workers | % of Total |
|---|---|---|---|---|
| Clerical support workers (4) | 8.5/10 | 2.5/10 | 151k | 5.2% |
| Professionals (2) | 6.5/10 | 1.5/10 | 222k | 7.7% |
| Managers (1) | 5.5/10 | 1.5/10 | 59k | 2.0% |
| Technicians and assoc. professionals (3) | 5.5/10 | 3.5/10 | 146k | 5.0% |
| Service and sales workers (5) | 3.5/10 | 4.5/10 | 798k | 27.6% |
| Skilled agricultural workers (6) | 3.0/10 | 6.5/10 | 206k | 7.1% |
| Plant and machine operators (8) | 3.0/10 | 7.5/10 | 213k | 7.4% |
| Armed forces occupations (0) | 2.5/10 | 3.0/10 | 18k | 0.6% |
| Craft and related trades workers (7) | 2.5/10 | 4.5/10 | 399k | 13.8% |
| Elementary occupations (9) | 2.0/10 | 5.5/10 | 682k | 23.6% |
El Salvador's maquila sector - employing around 80,000 in textile assembly - scores low on AI exposure (2.5-3.0/10) but faces real robotics risk (7.5/10 for plant operators) as garment automation matures. The timeline is longer than AI adoption but the trajectory is the same: US brands reshoring with automation rather than nearshoring with human labor.
What this means for Salvadoran workers
For most Salvadoran workers, the immediate AI story is background noise. The 682,000 elementary workers, 399,000 craft workers, and 798,000 service and sales workers face economic pressures far more pressing than AI automation: wage stagnation, gang violence affecting labor mobility, and competition from informal sector workers. AI is not their near-term displacement risk.
The workers who should pay attention are the 151,000 in clerical roles and the 222,000 professionals. For clerical workers in BPO and banking, the displacement timeline is set by US corporate procurement cycles - when a US client decides to automate their claims processing or data entry workflow, the Salvadoran workers handling those tasks face direct impact within 12-24 months. Building Spanish-English bilingual project management skills, moving into client relationship roles, and developing oversight capabilities for AI tools are the most durable career responses available.
Explore El Salvador's full workforce breakdown
AI exposure, robotics risk, and employment data for all El Salvador occupation groups.
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Methodology
Employment figures are from ILO ILOSTAT (CC BY 4.0), based on DIGESTYC El Salvador's EHPM, using ISCO-08 major group classifications. Data covers approximately 2.89 million Salvadoran workers. AI exposure scores are research-based estimates per ISCO-08 group, informed by Frey-Osborne (Oxford), OECD, and IMF studies on task-level automation. They reflect the proportion of an occupation's core tasks that current AI can perform or significantly augment - not predictions of job loss rates.
Frequently asked questions
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Related analyses
Data sources
- ILO ILOSTAT - Employment by sex, occupation (ISCO-08), El Salvador (CC BY 4.0)
- DIGESTYC El Salvador - Encuesta de Hogares de Propositos Multiples (EHPM)
- Frey, C.B. and Osborne, M.A. (2017). The future of employment. Technological Forecasting and Social Change.
- OECD - The Future of Work and Skills
- IMF - Gen-AI: Artificial Intelligence and the Future of Work (2024)