AI & jobs · Province in South Africa
Eastern Cape
27%
of jobs here are estimated to be exposed to generative AI, below the national 27% (−0.4 pts).
MODEL5th of 9 regions564K exposed workers
Key numbers
PopulationWIKIDATA
7.2M
as of 2022
Share of national populationWIKIDATA
11.7%
3rd largest of 9
People in workMODEL
2.1M
national total × population share
Highest-exposure jobsMODEL
6.0%
national 6.1%
Area
169K km²
43 people per km²
Settlement patternMODEL
Mixed
32% live in major cities
Largest city
Port Elizabeth
1M (metro)
Mapped towns & cities
14
Natural Earth places
AI use
ANTHROPICClaude.ai conversations, April–May 2026.
Usage intensityANTHROPIC
0.17×
usage share ÷ population share
Share of national useANTHROPIC
2.0%
11.7% of population
Work-relatedANTHROPIC
27%
national 45%
Automation-styleANTHROPIC
43%
national 51%
Augmentation 57%Automation 43%
Sector mix
MODELEstimated share of jobs by sector, against the national mix.
Eastern Cape
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
- KwaZulu-Natal 27% exposed
- Western Cape 28% exposed
- Limpopo 24% exposed
- Mpumalanga 25% exposed
- North West 26% exposed
- Free State 27% exposed
- Northern Cape 25% exposed