AI & jobs · Country profile
Tanzania
10%
of jobs are in occupations exposed to generative AI. That's about 3.5M people.
MODEL179th of 183 most exposed
World 21%Lower-middle income 16%
Key numbers
Workers in exposed jobsMODEL
3.5M
of 33.5M in work
Highest-exposure jobsMODEL
0.6%
208K people
People in workILO
33.5M
49% women
UnemploymentWORLD BANK
1.6%
2025
Youth unemploymentWORLD BANK
2.4%
ages 15–24
GDP per capitaWORLD BANK
$1,319
US$, 2025
Internet usersWORLD BANK
31%
of population
AI preparednessIMF
0.35
126th of 165
PopulationWORLD BANK
70.5M
Tertiary enrolmentWORLD BANK
4%
gross ratio
Vulnerable employmentWORLD BANK
84%
own-account & family workers
Urban populationWORLD BANK
37%
Women and men
MODELBased on the real occupation mix of women’s and men’s jobs (ILO).
Women are +0.8 pts more exposed, mostly because they hold more clerical and administrative jobs.
How it compares
MODELAI preparedness
IMFTanzaniaLower-middle income average
IMF AI Preparedness Index (2023). The four parts sum to the overall score of 0.35 (0–1 scale).
Exposure vs preparedness
Tanzania is highlighted. The other dots are all countries with both measures.
Sources: ILO modelled estimates 2025 · World Bank WDI · IMF AIPI · Anthropic Economic Index · Wikidata · Natural Earth. How the estimates are made.
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
- Katavi 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