Healthcare affordability remains a critical challenge across Africa, straining payers, providers and patients.
As the push for Universal Health Coverage (UHC) intensifies, costs are rising. In Kenya alone, household medical expenses surged by 3.3 percent in the past year, driven by higher fees, drug prices and insurance premiums.
By enhancing efficiency, enabling early diagnosis, and optimising resources, Artificial Intelligence (AI) can significantly lower healthcare costs and ease the impact of severe health worker shortages.
The most cost-effective treatment is the one never needed. AI excels in preventive care by analysing patient data - medical history, demographics and lifestyle factors - to identify high-risk individuals.
This allows earlier diagnosis and timely intervention for conditions such as hypertension and diabetes, empowering patients to manage their health before complications become severe and expensive.
AI is also improving diagnostics. In Morocco, tools such as Deep Echo analyse ultrasound images to detect fetal abnormalities early, enabling less invasive and more affordable treatment. In South Africa, AI-enhanced targeting for tuberculosis screening has sharply reduced the cost of identifying active cases.
For millions in rural areas, access to a doctor remains limited, underscoring the need to extend care beyond hospitals.
AI is helping to dismantle these barriers through telehealth. Smartphone applications can assess symptoms and provide initial guidance, while wearable devices remotely monitor patients with chronic conditions such as heart failure and chronic obstructive pulmonary disease (COPD).
In Rwanda, the Babyl platform uses AI triage to connect patients with appropriate care, reducing unnecessary hospital visits by 54 percent. In South Africa, Vula Mobile supports community health workers with instant diagnostic guidance, cutting unnecessary specialist referrals by 67 per cent. This shift reduces costly admissions and follow-up visits.
Sub-Saharan Africa carries 24 percent of the global disease burden but has only 3 percent of the world’s healthcare workers.
With the World Health Organisation projecting a global shortfall of 11 million health professionals by 2030, AI-driven automation is increasingly essential. It can streamline supply chains, reduce administrative burdens through automated documentation and billing, and allow clinicians to focus on patients.
In Ghana, mPharma uses predictive analytics to cut drug stockouts by over 45 percent, lowering patient costs.
Rwanda’s Viebeg Technologies reduces waste by improving procurement efficiency. In Kenya, M-Tiba has used AI to accelerate insurance claim approvals.
However, challenges remain. Limited internet access, unreliable electricity, and a lack of digitised data constrain adoption. High upfront costs and reliance on data from Western contexts also limit effectiveness. Even so, Africa’s growing health-tech ecosystem signals a shift towards more efficient, equitable, and affordable healthcare systems.
Dr Aluoch is a consultant physician
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