The World Bank publishes the first rigorous study (RCT) evaluating the impact of generative AI on education in Sub-Saharan Africa. The intervention: a six-week after-school tutoring program using Microsoft Copilot (GPT-4) for English learning among first-year secondary school students in Benin City, Nigeria.
Transformative results: The study demonstrates substantial improvements despite significant infrastructure constraints. The overall score increases by 0.31 standard deviation, English by 0.23 standard deviation (equivalent to 1.5 years of typical Nigerian schooling), AI knowledge by 0.31 standard deviation. Overall gains are equivalent to two years of schooling. A linear dose-response relationship shows that each additional day of attendance generates +0.031-0.033 standard deviation of improvement.
Notable differentiated effects: Girls benefit from an additional 0.42 standard deviation effect, offsetting initial performance gaps. Students with higher baseline scores and those from more advantaged socio-economic backgrounds show larger gains, but disadvantaged students also achieve statistically significant improvements.
Exceptional cost-effectiveness: At $48 per student for six weeks ($124 annualized), the intervention generates 3.2 equivalent years of schooling (EYOS) per $100 invested, surpassing most comparable educational interventions worldwide. The benefit-cost ratio reaches 161:1 to 260:1. Projected lifetime wage returns reach $7,767-$12,517 per participant.
Structured pedagogical approach: The success relies on three days of teacher training, prompts designed according to learning science principles (retrieval practice, elaborative interrogation), awareness of AI hallucinations and biases, and active supervision of student engagement. The teacher acts as a "force multiplier" rather than being replaced.
Promising scalability: The use of free software (no subscription), the absence of any need for proprietary question banks, and success with non-specialized staff suggest strong replication potential. The study addresses Bloom's "two-sigma problem": how to make the benefits of personalized tutoring accessible at the scale of entire populations in an economically viable way.
Critical context: The study is set within the global learning crisis, where 70% of ten-year-olds in low- and middle-income countries cannot read a text appropriate to their level. These results position generative AI tutoring as a promising approach for resource-constrained contexts.