Keypoints
- Salient Advisory has released a report identifying seven major health supply chain challenges where artificial intelligence (AI) can deliver significant impact.
- The report found that existing AI solutions are already addressing five of the seven critical bottlenecks across Africa.
- AI-enabled platforms have reportedly generated $38 million in procurement savings in Ethiopia, reduced procurement planning time in Kenya to under one hour, and lowered inventory levels in Morocco by 20%.
- Salient Advisory is urging governments and global health organisations to invest in AI infrastructure, policy frameworks and technical capacity.
- The firm also called for stronger evidence on the cost impact of AI to support wider adoption across Africa.
Main Story
Healthcare consulting firm Salient Advisory has called for accelerated adoption of artificial intelligence (AI) to improve health supply chains across Africa, saying early deployments are already demonstrating measurable gains in procurement efficiency, inventory management and supply chain planning.
The recommendation is contained in the firm’s newly released report, “AI Applications in African Health Supply Chains,” which examines how AI technologies are being deployed to address longstanding supply chain challenges affecting healthcare delivery across the continent.
According to the report, African health supply chains continue to face persistent systemic bottlenecks, while declining official development assistance has increased the urgency for more efficient and technology-driven solutions.
Drawing on contributions from supply chain leaders across global health institutions, the report identifies seven major health supply chain challenges where AI appears most capable of delivering immediate impact. It also maps 20 AI solutions currently deployed within health supply chains and highlights several initiatives already producing measurable outcomes in African markets.
Among the reported impacts, Opian Technologies’ ForLab Plus platform, deployed by Ethiopia’s Ministry of Health and the Ethiopian Pharmaceutical Supply Service across more than 5,700 public health facilities, reportedly reduced planned procurement expenditure by approximately $38 million through consumption-based forecasting at the facility level.
In Nigeria, a pilot project led by the Global Fund in partnership with AI company V7 Labs reportedly achieved an 87% reduction in document processing and manual review time for a fourth-party logistics provider. The initiative also reduced invoice-to-payment processing time from 13 days to three days, saving an estimated 960 work hours.
In Kenya, InSupply Health’s SMArT platform, developed in collaboration with the Ministry of Health, reportedly reduced procurement planning time from two to three days to less than one hour per health facility.
Similarly, Distripha’s AI-powered inventory planning solution helped private pharmacies in Morocco reduce overall stock levels by 20%, improving inventory efficiency.
Based on these findings, Salient Advisory called on governments, development partners and global health organisations to expand investments in AI infrastructure, strengthen local technical capacity and establish policy frameworks that support responsible adoption of AI across health systems.
The firm also recommended that governments develop supply chain cost baselines before implementing AI solutions and modernise procurement processes to ensure AI-generated insights can effectively support decision-making.
In addition, the report urged development partners to fund independent studies that assess the cost-effectiveness of AI solutions, noting that stronger evidence would help accelerate broader adoption across African healthcare systems.
The Issues
Despite encouraging early results, AI adoption across African health supply chains remains at an early stage, with limited independent evidence on long-term cost savings and system-wide impact.
The report highlights the need for improved access to AI infrastructure, stronger policy and regulatory frameworks, and greater investment in local AI expertise to ensure African countries can fully benefit from emerging technologies.
It also stresses the importance of independent verification of AI performance, noting that many reported outcomes are based on self-reported deployment data from solution providers.
What’s Being Said
Director of Supply Chain at Salient Advisory, Deji Ogunye, said:
“Early evidence suggests AI solutions are delivering measurable results in specific contexts, offering health systems a promising path to do more with less. But self-reported results from a limited number of deployments are not yet sufficient on their own to drive adoption at scale.”
He added that coordinated action—including stronger impact evidence and supportive policy frameworks—would be required to move AI adoption from isolated deployments to system-wide transformation.
Senior Program Officer at the Gates Foundation, Ann Allen, said:
“This report offers a valuable evidence base for how AI is already being applied to real supply chain challenges across the continent and flags the need for timely action to ensure promising AI innovations in Africa have equitable access to AI infrastructure.”
She expressed optimism about continued collaboration among stakeholders to build on the early successes identified in the report.
What’s Next
Salient Advisory is encouraging governments, development agencies and healthcare organisations to accelerate investments in AI infrastructure, policy development and technical capacity while supporting independent research on the economic impact of AI solutions.
As more AI-powered health supply chain initiatives are deployed, stakeholders are expected to monitor their effectiveness and build a stronger evidence base to support broader adoption across Africa’s healthcare systems.
Bottom Line
The Salient Advisory report suggests that artificial intelligence is beginning to deliver measurable improvements in Africa’s health supply chains, from procurement and inventory management to operational efficiency. However, scaling these gains will depend on stronger evidence, supportive policies and sustained investment in AI infrastructure and local innovation.
 to improve health supply ...){kind=link}