AI & jobs · Region in Tanzania
Katavi
10%
of jobs here are estimated to be exposed to generative AI, below the national 10% (−0.8 pts).
MODEL17th of 30 regions61.4K exposed workers
Key numbers
PopulationWIKIDATA
1.2M
as of 2022
Share of national populationWIKIDATA
1.9%
24th largest of 30
People in workMODEL
639K
national total × population share
Highest-exposure jobsMODEL
0.5%
national 0.6%
Area
47.8K km²
24 people per km²
Settlement patternMODEL
Mixed
8% live in major cities
Largest city
Mpanda
73.3K (metro)
Mapped towns & cities
2
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
MODELEstimated share of jobs by sector, against the national mix.
Katavi
Tanzania
Exposed workers by sector
MODELRanking in Tanzania
MODELBy modelled AI exposure, out of 30 regions.
About these estimates. No source publishes AI exposure by region for every country. The model splits Tanzania'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 Tanzania
- Dar es Salaam 15% exposed
- Mwanza 11% exposed
- Tabora 9% exposed
- Morogoro 10% exposed
- Dodoma 10% exposed
- Kagera 9% exposed
- Geita 8% exposed
- Tanga 10% exposed
- Kigoma 10% exposed
- Mara 10% exposed
- Arusha 11% exposed
- Mbeya 11% exposed
- Shinyanga 10% exposed
- Simiyu 8% exposed
- Pwani 10% exposed
- Singida 9% exposed
- Manyara 9% exposed
- Kilimanjaro 13% exposed
- Ruvuma 10% exposed
- Mtwara 10% exposed
- Rukwa 10% exposed
- Lindi 9% exposed
- Iringa 10% exposed
- Mjini Magharibi 14% exposed
- Njombe 9% exposed
- North Pemba 11% exposed
- South Pemba 12% exposed
- Unguja North 8% exposed
- Unguja South 8% exposed