Timor-Leste AI Job Risk 2026: Which of 357k Workers Are Most Exposed?

357,150 workers, DGE Labour Force Survey 2022

Employment data comes from ILO ILOSTAT (CC BY 4.0), based on the Direcao-Geral de Estatistica (DGE) Timor-Leste, Labour Force Survey 2022. ISCO-08 major group classifications. The 2022 data is recent and captures the post-COVID recovery period and the political transition to a new government under Xanana Gusmao (elected April 2023, following the May 2022 elections). The DGE Labour Force Survey methodology follows ILO standards and covers employed persons across the 13 districts of Timor-Leste, including Dili, Baucau, Bobonaro, Ermera, Aileu, Ainaro, Manufahi, Liquica, Manatuto, Covalima, Oecusse, Viqueque, and Lautem. Coverage of subsistence agricultural activities in remote highland districts - particularly the mountainous interior of Ermera and Ainaro - relies on enumerator assessments that may undercount the most isolated communities.

Timor-Leste's economy has been shaped by two defining forces since independence. The first is oil and gas revenue: the Bayu-Undan field in the Timor Sea, operated by ConocoPhillips, was the primary revenue source from the early 2000s until it was depleted around 2023. Oil revenues flowed into the Petroleum Fund of Timor-Leste, which was used to fund government expenditure - including the civil service salaries and infrastructure spending that created most of the formal employment in Dili. The Greater Sunrise development, a larger gas field shared with Australia, remains contested through the Timor Sea Maritime Boundary Treaty (finalised 2018 through PCA arbitration) but has not yet begun production. The depletion of Bayu-Undan without Greater Sunrise coming online creates a fiscal sustainability challenge that directly affects the capacity of the government to expand the formal employment base.

The second force is subsistence agriculture. Timor-Leste has a mountainous, rugged interior across districts such as Ermera (the largest coffee-producing region, accounting for most of the country's main cash export crop), Ainaro, and Manufahi. Subsistence farming of maize, cassava, sweet potato, and rice, combined with livestock keeping, is the primary livelihood activity for the majority of households outside Dili. The ILO Labour Force Survey captures this activity within the skilled agricultural, forestry and fishery workers classification - explaining why agriculture dominates the data and why the overall AI exposure average is so low.

The most AI-exposed jobs in Timor-Leste

Clerical support workers score 8.5/10 on AI exposure in Timor-Leste, and their 0.76% share - just 2,720 workers - is among the smallest clerical proportions in the WorldJobsData dataset across 206 countries. For comparison, Indonesia, the country that occupied Timor-Leste from 1975 to 1999, shows a clerical share of approximately 5-6%, reflecting decades of administrative state-building. Timor-Leste's administrative infrastructure is still being developed, with significant support from Australian and international donor programmes. The clerical workers who exist are concentrated in government ministry offices in Dili, the banking sector (BCTL, BNU, Mandiri), and the few larger private sector employers operating in the capital.

Professionals at 6.5/10 (20,170 workers, 5.65%) are the group with the most meaningful AI exposure risk. Teachers form the largest sub-category within this group. The national education system was substantially rebuilt after the destruction of 1999, when Indonesian forces and pro-Indonesia militias destroyed approximately 70-80% of infrastructure across the country including most school buildings (UNDP estimates). The school system now covers primary education across all 13 districts, with secondary schools in district capitals and the national university (UNTL) and several private higher education institutions in Dili. Teachers in this system face the same AI augmentation pressure that is becoming visible in Indonesian, Australian, and Portuguese education systems - AI-assisted lesson preparation, language translation (Tetum and Portuguese are official languages, with Bahasa Indonesia and English also widely used), and automated assessment tools. The pathway into Timor-Leste is likely through Portuguese and Indonesian EdTech platforms that already serve the language communities Timor-Leste educators use.

Health workers at Hospital Nacional Guido Valadares in Dili and the network of district health centres and community health posts (CHPs) face diagnostic support tools and administrative AI that are being introduced into Pacific and Southeast Asian health systems through Australian Government (DFAT) and World Health Organization (WHO) development partnerships. Technicians and associate professionals at 5.5/10 (8,730 workers, 2.44%) include laboratory technicians at health facilities, engineering technicians in the infrastructure sector, and ICT technicians supporting the government network and the small but growing private telecommunications sector. Managers at 5.5/10 (data not separately reported at sufficient precision in the 2022 LFS) cover both formal business managers in Dili and cooperative and community organisation leaders classified under ISCO-08 major group 1.

The safest jobs in Timor-Leste

Elementary occupations score 2.0/10 on AI exposure - covering 18,800 workers at 5.26% of employment. This group includes domestic workers, cleaners, basic construction labourers, agricultural day labourers, and street vendors in Dili's Mercado Lama and the informal markets across district capitals. The physical and non-routine character of elementary work, combined with Timor-Leste's limited connectivity outside Dili, means that current AI has no pathway to disrupting these roles. Power supply in rural districts relies on diesel generators and limited grid connections; internet access outside Dili is patchy. These infrastructure constraints are independent protection against AI tools reaching rural elementary workers even if the technology were ready to automate their tasks.

Craft and related trades workers score 2.5/10 (14,040 workers, 3.93%). Construction activity - driven by government infrastructure spending and donor-funded projects - has made construction workers one of the more visible craft sub-categories in Dili. Carpenters, masons, electricians, and plumbers working on school reconstruction, health post building, and road maintenance projects are in this category. Mechanics maintaining the growing vehicle fleet on the Dili-Baucau highway corridor and artisanal food processing workers are also included. Armed forces occupations score 2.5/10 (2,820 workers, 0.79%) - the Forcas de Defesa de Timor-Leste and the Policia Nacional de Timor-Leste (PNTL) employ physical and operational workers whose roles are not amenable to AI automation on any current or near-term basis.

The dominant group protecting the overall AI exposure average is skilled agricultural, forestry and fishery workers (ISCO major group 6) - estimated at approximately 60-65% of employment based on the 3.32/10 weighted average and the known scores of all other groups. Coffee farming in Ermera District - where Timorese arabica coffee is exported under the Cooperativa Cafe Timor (CCT) and several fair-trade channels - is the main cash crop activity. Maize, cassava, and rice subsistence farming across the mountain districts, combined with coastal fishing across the 1,500 kilometres of coastline, fills the majority of this group. Current AI has no practical reach into these activities given Timor-Leste's terrain, connectivity, and input constraints. The comparison with Papua New Guinea is relevant: PNG shows a similar agricultural-dominated structure and a comparable low AI exposure average.

What this means for Timor-Leste workers

Timor-Leste's 3.32/10 weighted average is one of the lowest AI exposure scores in the WorldJobsData dataset, and the structure of the workforce explains why. When the majority of workers are in subsistence agriculture and fishing - activities scoring 3.0/10 on AI exposure - the aggregate national risk is inevitably low. This is not a sign of technological readiness or economic insulation; it reflects the weight of agricultural livelihoods in a young country that is still developing its formal economy. The fiscal challenge of post-Bayu-Undan oil depletion means that government-funded formal employment growth - which would increase the professional and clerical shares and thus raise the AI exposure average over time - is constrained. Greater Sunrise development, if it proceeds, would change this trajectory substantially by funding expanded public services and infrastructure that create formal employment.

For the 5.65% of workers who are professionals - 20,170 people - the AI risk is real and worth monitoring over a 5-10 year horizon. Teachers face the earliest AI augmentation pressure as Portuguese and Indonesian language EdTech tools become more capable and reach Timor-Leste schools through development programme technology transfer. The Australia connection is particularly relevant: Australian Aid (DFAT) funds significant education and health programmes in Timor-Leste, and technology pilots in Australian systems will eventually be introduced into Timorese partner institutions. Health workers face diagnostic support and administrative AI tools that are being rolled out across Southeast Asian health systems. The near-term impact is on the documentation and administrative side of professional work; deeper augmentation of teaching delivery and clinical judgment will take longer to reach Timor-Leste's institutions given infrastructure constraints.

For the 0.76% of workers in clerical roles - just 2,720 people - the 8.5/10 AI exposure score is severe but the group is so small that the aggregate national impact is limited. Workers in government ministries and the banking sector who are in early-career clerical positions should note that document processing automation and data entry AI are already standard in the Australian and Portuguese government systems that serve as institutional models for Timor-Leste. The Digital Timor-Leste agenda - supported by development partners - is likely to bring more administrative technology into government offices over the coming decade, increasing pressure on purely clerical roles even at a gradual pace. For the large majority of Timor-Leste workers - those in agriculture, elementary occupations, and craft trades - near-term AI risk is very low, and the more relevant challenges are productivity, market access for agricultural products, and infrastructure that enables economic participation rather than anything to do with artificial intelligence. Compare with Indonesia for context on how a more economically developed Southeast Asian neighbour faces a substantially different AI risk profile driven by a much larger formal employment sector. See also the US analysis and US vs World comparison for a baseline against the highest-exposure economies.