Sri Lanka's approximately 7.82 million workers score a weighted average AI exposure of 3.53/10, reflecting a workforce composition that is more service and knowledge-oriented than many South Asian neighbours - a well-educated workforce, a significant IT and BPO export sector generating $1.1 billion annually, and English-language capability that in principle puts Sri Lankan professionals in direct competition with AI tools marketed to the same client base. But the country's risk velocity of just 0.9/10 - one of the slowest disruption timelines in the entire dataset - tells a different story about the near-term pace of that exposure actually being realised. The reason is the 2022 economic crisis: the worst in Sri Lanka's post-independence history, it triggered an IMF $2.9 billion bailout, forced the sitting president to flee the country, caused severe fuel and power shortages, and accelerated emigration of educated young workers to Australia, the UK, and the Middle East. Rather than accelerating AI adoption, the crisis degraded the institutional capacity, capital availability, and digital infrastructure investment that AI deployment in an economy actually requires. Sri Lanka is recovering, but the workforce of 2026 is not the same as 2021, and neither is its capacity to adopt new technology quickly.
Sri Lanka's occupation data comes from ILO ILOSTAT and the Department of Census and Statistics (DCS) Sri Lanka Labour Force Survey 2025. The DCS is Sri Lanka's official national statistics authority and conducts quarterly LFS surveys using ISCO-08 occupation classification. The dataset covers approximately 7.82 million workers in Sri Lanka's formal and semi-formal economy. Sri Lanka's relatively high literacy rate (approximately 92% per DCS 2023) and long history of public sector employment create an occupation mix that tilts more toward clerical and professional work than most South Asian economies of comparable income level.
| Occupation Group | AI Score | Workers (est.) | Share (est.) |
|---|---|---|---|
| Clerical support workers (ISCO 4) | 8.5/10 | ~283K | ~3.6% |
| Professionals (ISCO 2) | 6.5/10 | ~589K | ~7.5% |
| Managers (ISCO 1) | 5.5/10 | ~340K | ~4.3% |
| Technicians and associate professionals (ISCO 3) | 5.5/10 | ~686K | ~8.8% |
| Service and sales workers (ISCO 5) | 3.5/10 | ~979K | ~12.5% |
| Skilled agricultural workers (ISCO 6) | 3.0/10 | ~1.087M | ~13.9% |
| Plant and machine operators (ISCO 8) | 3.0/10 | ~784K | ~10.0% |
| Craft and related trades (ISCO 7) | 2.5/10 | ~1.078M | ~13.8% |
| Armed forces (ISCO 0) | 2.5/10 | ~41K | ~0.5% |
| Elementary occupations (ISCO 9) | 2.0/10 | ~1.957M | ~25.0% |
Within clerical support (ISCO 4), Sri Lanka's large public sector creates a high concentration of administrative clerks in government ministries, provincial councils, and state-owned enterprises. The Sri Lankan government employs approximately 1.5 million people in total public service - one of the highest ratios relative to population in South Asia. Administrative clerks processing government forms, citizen service requests, and document verification across these agencies are the most directly exposed sub-group. AI tools for document processing and government workflow automation are already deployed in more advanced economies and are likely to reach Sri Lanka's public sector within a 3-5 year horizon.
Professionals at approximately 7.5% of the workforce is elevated for the region and directly reflects the IT/BPO sector. Colombo's IT corridor - including Orion City, Trace Expert City, and the emerging Port City development - hosts Sri Lankan companies including WSO2 (open source integration platform, Ballerina programming language), Virtusa (digital engineering services), IronOne Technologies, and dozens of smaller software firms. Sri Lanka's SLASSCOM (Sri Lanka Association of Software and Services Companies) reported approximately $1.1 billion in IT/BPO service exports in 2024, employing an estimated 80,000 to 100,000 direct workers in software development, QA testing, data annotation, and business process outsourcing. ICT professionals (ISCO 25) at this sub-group level score 8.5/10 on AI exposure - meaning the sector that is Sri Lanka's primary growth engine is also among the most AI-exposed in the economy.
Sri Lanka's 2022 economic crisis was triggered by a combination of factors: foreign exchange reserves depleted to near zero, an ill-timed transition to organic-only agriculture in 2021 that collapsed rice and tea yields, COVID-19 elimination of tourism revenues (normally $3-4 billion annually), and accumulated government debt. The crisis caused fuel rationing with queues stretching kilometers, electricity blackouts of up to 13 hours per day, medicine shortages in public hospitals, and eventually the storming of the presidential palace by protesters in July 2022. President Gotabaya Rajapaksa fled to the Maldives and then Singapore before resigning.
The IMF's $2.9 billion Extended Fund Facility approved in March 2023 stabilised the macroeconomic situation. By 2025, Sri Lanka's economy had returned to modest growth, inflation had fallen from a peak of 70%+ in September 2022 to single digits, and foreign reserves had partially recovered. But the social consequence most relevant to this analysis is the acceleration of professional emigration. Tens of thousands of educated young Sri Lankans - IT workers, doctors, engineers, nurses - left for Australia, Canada, the UK, Germany, and the Gulf between 2021 and 2024. The DCS estimates net emigration of 200,000 to 400,000 workers over this period, disproportionately concentrated in the professional and technical groups that score highest on AI exposure.
The Colombo Port City - a $1.4 billion Chinese-funded reclaimed land project and Special Economic Zone adjacent to Colombo's central business district - represents the most significant structural bet on Sri Lanka's post-crisis economic trajectory. The Port City is designed to host international financial services, law firms, and digital economy companies under a separate regulatory framework (the Colombo Port City Economic Commission Act 2021). If the Port City reaches its development targets, it would add substantially to the professional and financial services workforce with high AI exposure. Remittances at approximately $3.5 billion annually (2024 per Sri Lanka's Central Bank) now form the largest single source of foreign exchange, reflecting the scale of the diaspora workforce - which itself signals the skills pool that emigrated.
Sri Lanka's agricultural sector - concentrated in tea, rubber, coconut, and rice - elementary occupations, and physical trades workforce represent approximately 53% of the total employed at below 3.0/10 AI exposure.
| Occupation Group | AI Score | Workers (est.) | Share (est.) |
|---|---|---|---|
| Elementary occupations (ISCO 9) | 2.0/10 | ~1.957M | ~25.0% |
| Craft and related trades (ISCO 7) | 2.5/10 | ~1.078M | ~13.8% |
| Skilled agricultural workers (ISCO 6) | 3.0/10 | ~1.087M | ~13.9% |
| Plant and machine operators (ISCO 8) | 3.0/10 | ~784K | ~10.0% |
Elementary occupations at 25% - the largest single major group in the economy - and agricultural workers at approximately 14% are concentrated in the Hill Country tea estates (Nuwara Eliya, Kandy, Badulla districts), rubber cultivation in the southwest, and rice paddy farming in the dry zone. Sri Lanka's tea industry - producing approximately 280,000 tonnes annually and a major export earner - employs over 100,000 estate workers directly in plucking, processing, and grading. Tea plucking is among the most difficult agricultural tasks to automate due to the selectivity required (only the top two leaves and a bud are plucked) and the steep, wet terrain of the Hill Country. These workers score 3.0/10 on AI exposure and face minimal near-term AI software displacement risk. Craft and trades workers at approximately 14% - including construction workers, garment machinists in the apparel export sector, and auto mechanics - similarly face low AI exposure at 2.5/10.
Sri Lanka's 3.53/10 average combined with a 0.9/10 risk velocity is a genuinely unusual pairing: real exposure in the occupation mix, but very little near-term capacity for that exposure to translate into actual AI deployment. The IT/BPO sector - which built Sri Lanka's most successful post-tea export industry and employs tens of thousands of graduates - has the occupational profile that would normally put it directly in the path of AI automation of software testing, data annotation, code documentation, and business process tasks. But the same 2022 crisis that accelerated emigration of skilled workers also degraded the foreign-exchange access, capital investment, and institutional stability that would be needed for Sri Lankan firms - or the multinational clients who outsource to them - to invest in fast AI deployment inside the country in the near term.
The dynamic playing out in Sri Lanka's IT sector is therefore slower-moving than the occupation-level exposure numbers alone would suggest. AI tools raise the long-run productivity expectation per worker and will eventually reduce demand for junior and mid-tier roles, but the pace at which Sri Lankan firms can actually adopt these tools - versus firms in more stable, better-capitalised economies - is constrained by the same post-crisis conditions affecting the rest of the economy. Sri Lankan firms that move up the value chain toward product development, AI implementation services, and domain-specific software (healthcare IT, logistics tech, fintech) will be better positioned over a longer horizon than those competing on high-volume, routine task outsourcing. WSO2's investment in its own programming language (Ballerina) and open-source integration platform is an example of this strategic shift - competing on intellectual property rather than labor cost.
Recovery resilience at 4.3/10 is below what Sri Lanka's underlying human capital would suggest in a stable scenario. The 2022 crisis degraded institutional capacity, drove out a cohort of high-skill workers who may not return, and increased public debt service obligations that constrain fiscal capacity for retraining investment. The Tertiary and Vocational Education Commission (TVEC) and the ICT Agency (ICTA) have active digital skills programs, but scaling these to meet a future structural shift in the IT sector is a multi-year challenge that current fiscal constraints make harder. Workers who build expertise in AI implementation, cloud infrastructure, and domain-specific software engineering will be better positioned once the recovery matures and AI adoption in Sri Lanka accelerates from its currently very low base; those who remain in data entry, basic QA testing, and routine BPO tasks have more runway than the sector's headline exposure scores alone would suggest, precisely because the country's capacity to deploy AI quickly is so constrained right now.
Interactive breakdown of every occupation group, sortable by AI exposure score and worker count.
View Sri Lanka DataYour reaction helps us understand what to cover next.
Thanks for your reaction!
Get new country analyses, data updates, and AI labour market insights. No spam - one email when something worth reading drops.
AI exposure, robotics, offshoring and work-from-home scores are model-estimated: an AI language model (Claude Opus 4.7) scored each ISCO-08 occupation group on 28 May 2026, guided by published research. They are informed judgements, not measurements, and not forecasts of job losses. "Risk velocity" and its time windows come from a digital-infrastructure index (broadband and secure servers), not from occupations or measured AI adoption. Read the full methodology and how the scores were checked.
Spotted an error or know a better source? Report it and we will check it against the source data.