Artificial intelligence is beginning to improve forecasting, procurement and inventory management across African health supply chains, offering governments and healthcare providers new tools to offset growing funding constraints, according to a report published on Tuesday by healthcare consulting firm Salient Advisory.
Key findings include:
- Existing AI solutions are addressing 5 of Africa’s 7 critical health supply chain bottlenecks
- ~$38 million saved in planned procurement expenditure in Ethiopia
- 20% reduction in stock levels at private pharmacies due to improved planning in Morocco
- 3 days to under 1 hour procurement time per facility in Kenya
The report, titled “AI Applications in African Health Supply Chains,” identifies seven major supply chain challenges where AI has shown the greatest potential to improve efficiency and maps 20 AI solutions already deployed across the continent.
The findings come as African health systems face mounting pressure following a sharp decline in official development assistance, increasing the need for technologies that can reduce costs and improve the delivery of medicines and medical supplies.
The report draws on interviews with supply chain leaders from global health organisations and examines AI applications ranging from demand forecasting and procurement planning to document processing and inventory optimisation.
Among the case studies cited, Ethiopia’s Ministry of Health and the Ethiopian Pharmaceutical Supply Service used Opian Technologies’ ForLab Plus platform across more than 5,700 public health facilities, helping reduce planned procurement expenditure by about $38 million through consumption-based, facility-level forecasting.
In Nigeria, a pilot programme led by the Global Fund and AI company V7 Labs for a fourth-party logistics provider reduced document processing and manual review time by 87%, saving approximately 960 hours while shortening invoice-to-payment cycles from 13 days to three days, according to the report.
In Kenya, InSupply Health’s SMArT platform, developed with the Ministry of Health, cut procurement planning time from two to three days to less than one hour per facility, while Morocco-based Distripha’s AI inventory planning model reduced stock levels at private pharmacies by 20%, the report said.
Despite the early gains, Salient Advisory said evidence of AI’s impact remains limited and called for broader investment in research and independent evaluation before governments and development partners adopt the technology at scale.
The consultancy urged global health organisations to support equitable access to AI infrastructure for African innovators, invest in locally developed AI capabilities and fund independent studies measuring the technology’s impact on supply chain costs.
It also recommended that African governments establish baseline supply chain costs before procuring AI systems, strengthen AI policy and regulatory frameworks, build internal technical expertise and modernise procurement processes to support AI-driven decision-making.
“Early evidence suggests AI solutions are delivering measurable results in specific contexts, offering health systems a promising path to do more with less,” said Deji Ogunye, director of Supply Chain at Salient Advisory.
“But self-reported results from a limited number of deployments are not yet sufficient on their own to drive adoption at scale. What’s needed now is coordinated action, from credible impact evidence to policy frameworks, to move from isolated deployments to system-wide transformation,” he said.
Ann Allen, Senior Program Officer at the Gates Foundation, said the report demonstrated how AI was already addressing practical supply chain challenges across Africa while highlighting the need for timely investment in computing infrastructure to ensure innovators on the continent are not left behind.
Healthcare supply chains across much of Africa have long struggled with inaccurate demand forecasting, procurement delays, inventory shortages and distribution bottlenecks, challenges that have become more pronounced as donor funding declines and governments seek more efficient ways to manage limited healthcare resources.
