AI Job Atlas
AI & jobs · District|Regencies in Timor-Leste

Oe-Cusse Ambeno

District|Regencies TL-OE
19%
of jobs here are estimated to be exposed to generative AI, below the national 21% (−2.3 pts).
MODEL4th of 13 regions6,810 exposed workers

Key numbers

PopulationWIKIDATA
68.9K
as of 2015
Share of national populationWIKIDATA
5.9%
7th largest of 13
People in workMODEL
36.8K
national total × population share
Highest-exposure jobsMODEL
1.4%
national 1.7%
Area
742 km²
93 people per km²
Settlement patternMODEL
Rural
0% live in major cities
Mapped towns & cities
0
Natural Earth places

AI use

The Anthropic Economic Index does not publish usage for this region. Regions below a minimum number of sampled conversations are left out.

Sector mix

MODEL

Estimated share of jobs by sector, against the national mix.

Oe-Cusse Ambeno Timor-Leste
Agriculture 54.7%
Retail & wholesale 23.5%
Public admin 6.9%
Business services 3.1%
Transport & logistics 2.8%
Education 2.3%
Construction 1.9%
Other services 1.5%
Manufacturing 1.4%
Health & care 0.7%
Hospitality 0.6%
Finance 0.3%
Mining 0.1%
ICT & software 0.1%
Utilities 0.1%

Exposed workers by sector

MODEL
Retail & wholesale 2,562 Agriculture 1,543 Public admin 1,064 Business services 458 Education 404 Transport & logistics 203 Other services 151 Health & care 111

Ranking in Timor-Leste

MODEL

By modelled AI exposure, out of 13 regions.

1Dili 30% 2Ermera 19% 3Liquiçá 19% 4Oe-Cusse Ambeno 19% 5Baucau 18% 6Ainaro 18% 7Bobonaro 18%
About these estimates. No source publishes AI exposure by region for every country. The model splits Timor-Leste's real ILO sector employment across regions using population (Wikidata) and density: denser, capital-city regions get more finance, ICT and professional jobs, and rural regions more farming. Totals match national figures. AI usage figures are measured, not modelled. Methodology

Other regions of Timor-Leste

All of Timor-Leste →