AI & jobs · Country profile
Uganda
12%
of jobs are in occupations exposed to generative AI. That's about 2.8M people.
MODEL172nd of 183 most exposed
World 21%Low income 13%
Key numbers
Workers in exposed jobsMODEL
2.8M
of 22.8M in work
Highest-exposure jobsMODEL
0.7%
169K people
People in workILO
22.8M
48% women
UnemploymentWORLD BANK
2.8%
2025
Youth unemploymentWORLD BANK
4.2%
ages 15–24
GDP per capitaWORLD BANK
$1,206
US$, 2025
Internet usersWORLD BANK
9%
of population
AI preparednessIMF
0.35
125th of 165
PopulationWORLD BANK
51.4M
Tertiary enrolmentWORLD BANK
5%
gross ratio
Vulnerable employmentWORLD BANK
74%
own-account & family workers
Urban populationWORLD BANK
32%
Women and men
MODELBased on the real occupation mix of women’s and men’s jobs (ILO).
Women are +0.6 pts more exposed, mostly because they hold more clerical and administrative jobs.
How it compares
MODELAI preparedness
IMFUgandaLow income average
IMF AI Preparedness Index (2023). The four parts sum to the overall score of 0.35 (0–1 scale).
Exposure vs preparedness
Uganda 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 Uganda
- Maracha 12% exposed
- Wakiso 14% exposed
- Kampala 19% exposed
- Yumbe 11% exposed
- Mukono 11% exposed
- Kasese 14% exposed
- Isingiro 11% exposed
- Luwero 14% exposed
- Tororo 16% exposed
- Mayuge 11% exposed
- Ntungamo 12% exposed
- Kyenjojo 11% exposed
- Kamuli 12% exposed
- Mubende 12% exposed
- Buikwe 11% exposed
- Kyegegwa 11% exposed
- Bugiri 11% exposed
- Oyam 11% exposed
- Kayunga 13% exposed
- Kisoro 12% exposed
- Iganga 11% exposed
- Busia 15% exposed
- Mityana 14% exposed
- Buyende 11% exposed
- Rukungiri 11% exposed
- Kiryandongo 12% exposed
- Serere 11% exposed
- Rakai 10% exposed
- Masindi 14% exposed
- Masaka 15% exposed
- Kamwenge 11% exposed
- Pallisa 14% exposed
- Mpigi 12% exposed
- Lwengo 11% exposed
- Butaleja 11% exposed
- Zombo 11% exposed
- Namutumba 11% exposed
- Kanungu 11% exposed
- Ibanda 11% exposed
- Agago 10% exposed
- Sembabule 11% exposed
- Adjumani 14% exposed
- Nebbi 15% exposed
- Luuka 15% exposed
- Sironko 11% exposed
- Kole 11% exposed
- Mbale 18% exposed
- Kumi 13% exposed
- Kaliro 11% exposed
- Kabale 15% exposed
- Alebtong 11% exposed
- Bushenyi 11% exposed
- Bukedea 11% exposed
- Budaka 11% exposed
- Jinja 18% exposed
- Kyankwanzi 10% exposed
- Koboko 11% exposed
- Bududa 11% exposed
- Namayingo 10% exposed
- Soroti 11% exposed
- Bundibugyo 11% exposed
- Kaabong 10% exposed
- Sheema 11% exposed
- Amuria 10% exposed
- Nakaseke 10% exposed
- Kibuku 11% exposed
- Amuru 10% exposed
- Lira 17% exposed
- Pader 10% exposed
- Kitgum 15% exposed
- Kibaale 11% exposed
- Bulambuli 13% exposed
- Katakwi 12% exposed
- Kabarole 15% exposed
- Nakasongola 12% exposed
- Mitooma 11% exposed
- Apac 10% exposed
- Kalungu 11% exposed
- Nwoya 10% exposed
- Kotido 10% exposed
- Dokolo 11% exposed
- Ngora 11% exposed
- Lamwo 10% exposed
- Napak 10% exposed
- Amudat 11% exposed
- Gomba 11% exposed
- Bukomansimbi 11% exposed
- Amolatar 10% exposed
- Manafwa 11% exposed
- Kiboga 13% exposed
- Mbarara District 16% exposed
- Kiruhura District 10% exposed
- Rubirizi 10% exposed
- Buhweju 11% exposed
- Buliisa 10% exposed
- Otuke 10% exposed
- Arua 17% exposed
- Butambala 11% exposed
- Abim 10% exposed
- Hoima 10% exposed
- Kaberamaido 12% exposed
- Gulu 17% exposed
- Kapchorwa 11% exposed
- Lyantonde 11% exposed
- Kween 11% exposed
- Ntoroko 10% exposed
- Bukwo 11% exposed
- Nakapiripirit 10% exposed
- Buvuma 10% exposed
- Moyo 15% exposed
- Moroto 10% exposed
- Kalangala 12% exposed