AI Job Atlas
AI & jobs · District in Mauritius

Rivière Noire

District MU-BL
28%
of jobs here are estimated to be exposed to generative AI, below the national 30% (−1.2 pts).
MODEL16th of 16 regions7,334 exposed workers

Key numbers

PopulationWIKIDATA
76.6K
Share of national populationWIKIDATA
4.3%
12th largest of 16
People in workMODEL
25.8K
national total × population share
Highest-exposure jobsMODEL
5.3%
national 5.7%
Area
319 km²
240 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.

Rivière Noire Mauritius
Retail & wholesale 16.8%
Manufacturing 11.3%
Construction 9.2%
Business services 9.1%
Hospitality 8.7%
Public admin 7.6%
Other services 6.8%
Agriculture 6.8%
Transport & logistics 6.6%
Education 6.5%
Health & care 4.3%
Finance 2.7%
ICT & software 2.3%
Utilities 1.1%
Mining 0.2%

Exposed workers by sector

MODEL
Retail & wholesale 1,373 Public admin 902 Business services 880 Education 754 Hospitality 557 Manufacturing 486 Health & care 446 Other services 441

Ranking in Mauritius

MODEL

By modelled AI exposure, out of 16 regions.

10Port Louis 29% 11Grand Port 29% 12Flacq 29% 13Rodrigues 29% 14Moka 29% 15Savanne 29% 16Rivière Noire 28%
About these estimates. No source publishes AI exposure by region for every country. The model splits Mauritius'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 Mauritius

All of Mauritius →