|
Ask Viamo Anything — Voice-First Generative AI for Feature-Phone Users in Zambia |
Evidence: Observational / pre–post
|
Top 1% 100/100 |
Good practice |
Lusaka, Zambia |
— |
|
Zambia GEWEL — Girls' Education, Women's Empowerment and Livelihoods Programme |
Evidence: Descriptive / self-reported
|
Top 9% 96/100 |
Good practice |
Lusaka, Zambia |
— |
|
LinkNet / Macha Works — Zambia's Community-Owned Mesh Network and Rural ICT Academy |
Not assessed |
Top 10% 96/100 |
Good practice |
Macha, Zambia |
— |
|
eGranary Digital Library — Offline Access to Millions of Learning Resources for Zambia's Medical Schools |
Not assessed |
Top 24% 92/100 |
Good practice |
Lusaka, Zambia |
— |
|
University Teaching Hospital One-Stop Centre — Lusaka's Integrated Model for Child Sexual-Abuse and GBV Care |
Evidence: Observational / pre–post
|
Top 26% 85/100 |
Good practice |
Lusaka, Zambia |
— |
|
PRISE — CABI's AI-Powered Pest-Risk Forecasting Service for African Farmers |
Evidence: Quasi-experimental
|
Top 12% 80/100 |
Good practice |
Lusaka, Zambia |
— |
|
AVE — AI-Assisted Cervical Precancer Screening in Zambia's Public Health Facilities |
Evidence: Observational / pre–post
|
Top 12% 80/100 |
Good practice |
Lusaka, Zambia |
— |
|
BongoHive — Zambia's First Technology & Innovation Hub |
Evidence: Descriptive / self-reported
|
Top 27% 76/100 |
Good practice |
Lusaka, Zambia |
— |
|
IGC and ZamStats Use GPT Models to Speed Up Zambia's Labour Force Survey Coding |
Evidence: Quasi-experimental
|
Top 22% 73/100 |
Good practice |
Lusaka, Zambia |
— |
|
Rural ICT Hubs for Women and Girls (GRZ-UN Joint Programme on GBV) |
Evidence: Descriptive / self-reported
|
Top 55% 72/100 |
Good practice |
Chongwe, Zambia |
— |
|
Lusaka Sanitation Project — World Bank-Financed Sewer Upgrading for Zambia's Capital |
Evidence: Observational / pre–post
|
Top 50% 67/100 |
Good practice |
Lusaka, Zambia |
— |
|
Mulungushi University's IIOE Centre — Zambia's Generative AI Teacher Training and National AI-in-Education Policy Drive |
Evidence: Descriptive / self-reported
|
Top 14% 67/100 |
Good practice |
Kapiri Mposhi, Zambia |
— |
|
Luangwa Community Forests Project (Zambia) |
Evidence: Observational / pre–post
|
Top 7% 67/100 |
Good practice |
Chipata, Zambia |
— |
|
Zambia's Electoral Commission Strips 18,000 Duplicate Names from a 7-Million-Voter Biometric Register |
Not assessed |
Top 46% 60/100 |
Good practice |
Lusaka, Zambia |
— |
|
COMACO — Community Markets for Conservation (Zambia) |
Evidence: Quasi-experimental
|
Top 14% 60/100 |
Good practice |
Chipata, Zambia |
— |
|
ZRA AI Unit — Zambia Revenue Authority machine-learning platform for tax-fraud detection and revenue-gap identification |
Evidence: Descriptive / self-reported
|
Top 62% 53/100 |
Good practice |
Lusaka, Zambia |
— |
|
Zambia Development Agency — A Five-Agency Merger Aiming for One-Stop Investment Facilitation |
Evidence: Observational / pre–post
|
Top 83% 52/100 |
Good practice |
Lusaka, Zambia |
— |
|
Digital Zambia Acceleration Project — A $100M World Bank Push for Inclusive Digital ID and Connectivity |
Evidence: Descriptive / self-reported
|
Top 82% 52/100 |
Good practice |
Lusaka, Zambia |
— |
|
"Mother's Day" — Zambia's Statutory Monthly Menstrual Leave |
Not assessed |
Top 72% 48/100 |
Good practice |
Lusaka, Zambia |
— |
|
ZICTA's Universal Access Fund assistive-ICT package at Chinsali Special School, Zambia |
Evidence: Descriptive / self-reported
|
Top 86% 48/100 |
Good practice |
Chinsali, Zambia |
— |
|
AI Anomaly Detection Cuts Verification Errors in Zambia's Social Cash Transfer — A Copperbelt Pilot |
Not assessed |
Top 74% 47/100 |
Good practice |
Kitwe, Zambia |
— |
|
AI Base-Mapping of Lusaka Speeds Up Zambia's National Land Titling Programme in Informal Settlements |
Evidence: Descriptive / self-reported
|
Top 74% 47/100 |
Good practice |
Lusaka, Zambia |
— |
|
Girls in ICT Learn-A-Thon — Zambia's National AI, Cybersecurity and Data-Science Track for Schoolgirls |
Evidence: Descriptive / self-reported
|
Top 56% 47/100 |
Good practice |
Lusaka, Zambia |
— |
|
ZRA AI Unit — Zambia Revenue Authority's Machine-Learning Customs Risk Model |
Evidence: Descriptive / self-reported
|
Top 74% 47/100 |
Good practice |
Lusaka, Zambia |
— |