AI & jobs · Province in South Africa
KwaZulu-Natal
27%
of jobs here are estimated to be exposed to generative AI, below the national 27% (−0.2 pts).
MODEL4th of 9 regions978K exposed workers
Key numbers
PopulationWIKIDATA
12.4M
as of 2022
Share of national populationWIKIDATA
20.1%
2nd largest of 9
People in workMODEL
3.6M
national total × population share
Highest-exposure jobsMODEL
6.0%
national 6.1%
Area
94.1K km²
132 people per km²
Settlement patternMODEL
Mixed
30% live in major cities
Largest city
Durban
2.7M (metro)
Mapped towns & cities
7
Natural Earth places
AI use
ANTHROPICClaude.ai conversations, April–May 2026.
Usage intensityANTHROPIC
0.43×
usage share ÷ population share
Share of national useANTHROPIC
8.7%
20.1% of population
Work-relatedANTHROPIC
42%
national 45%
Automation-styleANTHROPIC
53%
national 51%
Augmentation 47%Automation 53%
Sector mix
MODELEstimated share of jobs by sector, against the national mix.
KwaZulu-Natal
South Africa
Exposed workers by sector
MODELRanking in South Africa
MODELBy modelled AI exposure, out of 9 regions.
About these estimates. No source publishes AI exposure by region for every country. The model splits South Africa'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 South Africa
- Gauteng 29% exposed
- Eastern Cape 27% exposed
- Western Cape 28% exposed
- Limpopo 24% exposed
- Mpumalanga 25% exposed
- North West 26% exposed
- Free State 27% exposed
- Northern Cape 25% exposed