Artificial Intelligence and Public Health in Africa

Artificial intelligence (AI) is now emerging as a major transformation lever across economic and social sectors, and public health is no exception. By reshaping diagnostics, treatments, care management and resource allocation, AI is redefining modern medicine.
Globally, the market for AI applied to healthcare is estimated at more than 20 billion dollars in 2024 and is recording annual growth of more than 40%. In Morocco, AI is already being deployed in several hospitals and startups, positioning the country 87th in the global AI readiness ranking, with significant development potential. This momentum opens the way to medicine that is more precise, personalized and accessible, particularly for systems facing structural challenges, as many African countries do.

The continent faces a critical shortage of health professionals, affecting more than 36 countries (WHO, 2023), as well as a resurgence of health emergencies. In this context, AI appears as a way to bridge human and technological gaps and promote more equitable access to care.

More Accurate Diagnostics and Better Prevention

One of the most remarkable contributions of artificial intelligence in medicine lies in its ability to significantly strengthen diagnostic accuracy while reducing time to care. For example, in Morocco, AI is used in radiology to analyze X-rays, MRIs and other images, helping radiologists detect abnormalities invisible to the human eye and make diagnoses more quickly, with accuracy reaching 95% to 99%. Diagnostic-support algorithms are also used to detect medical complexities such as lung nodules or breast microcalcifications, reducing human error and improving the quality of care received before and after surgery. Also in Morocco, the use of surgical robots such as Da Vinci helped reduce postoperative complications by 20% between 2020 and 2024.

On the other side of the continent, in Dakar, Abass Ndao University Hospital developed, in partnership with the French company GAIHA, software called Gaiha Prio Retino+™ that uses computer vision to automate screening for diabetic retinopathy from simple fundus images. This solution is genuinely innovative because it does not require heavy infrastructure or the presence of specialists, making it suitable for medical deserts in West Africa and significantly improving medical diagnosis in Dakar.

Beyond improving diagnostics, artificial intelligence plays a key role in health prevention and epidemic management. It makes it possible to identify infection clusters more quickly, anticipate their spread and guide strategic public-health decisions. The example of Mali illustrates this: during the Covid-19 pandemic, the District Health Information System 2 (DHIS2), strengthened by AI, made it possible to effectively target priority areas for vaccination, improving responsiveness and population safety.

Improving Access to Care in Africa Through AI

Africa has seen health emergencies increase by 40% since 2022, while endemic infectious diseases such as Ebola and malaria continue to weigh on fragile systems. In addition, several African countries face a critical shortage of medical personnel, limiting equitable access to care for much of the rural or isolated population. Faced with these challenges, AI is emerging as a crucial lever for improving both the quality and accessibility of care in hard-to-reach areas.

It can help offset the shortage of health professionals and better serve isolated and underserved areas. In many African regions, concrete AI applications have brought care closer to the most remote populations.

For example, in Rwanda, Ghana and Nigeria, the company Zipline uses AI-guided autonomous drones to deliver medicines, blood products and vaccines to remote regions, including areas that are difficult to access or affected by insecurity. This system has transformed medical distribution: in Rwanda, it reduced the waste of blood bags by 67% and shortened medicine delivery times by a factor of three to four. Similarly, in Ghana, where more than a third of maternal deaths are due to hemorrhage, drones make it possible to provide medicine delivery within 15 to 20 minutes by sending packages to hospitals.

In addition, through the deployment of telemedicine and remote diagnostic tools, patients can now receive diagnoses without having to travel. In Nigeria, for example, the Cervix AI application reaches a sensitivity of 94% for cervical cancer screening, even in centers without specialists. This advance represents a major turning point for countries facing high mortality linked to the lack of early detection of gynecological diseases.

The Other Side of Innovation: Why AI Still Struggles to Take Hold in African Health

Although artificial intelligence offers many advances in health, its sustainable implementation still faces several major obstacles:

• One of the greatest obstacles is the digital divide and lack of infrastructure. In many parts of Africa, access to reliable electricity remains limited, high-speed internet coverage is weak and suitable data centers are scarce. Africa accounts for only 3% of the world’s data centers. This shortage limits the deployment of complex algorithms developed to improve the quality of care.
• In addition, security, legal and governance issues must also be taken into account. To date, national and continental regulatory frameworks for governing the use of AI remain absent or weak, particularly when it comes to cybersecurity for health data. In Morocco, on April 8, 2025, the National Social Security Fund (CNSS) suffered a major cyberattack, leading to the leak of sensitive personal data belonging to nearly two million employees. This serious breach of critical systems illustrates the growing risks that public institutions must manage and underscores the urgent need to strengthen cybersecurity to protect the country’s health and social infrastructure.
• Finally, an equally important challenge is skepticism among health professionals and resistance to change. Many practitioners remain reluctant to adopt AI, either out of concern that their skills will be devalued or because they lack awareness of its practical benefits for clinical care. This cultural barrier slows the integration of digital tools into care pathways. In Senegal, for example, Dr. Aminata Faye stresses that while AI is promising, it must remain a support tool and not replace professionals. She also points to the difficulty of adapting tools to local realities, which contributes to notable reluctance toward these technologies.

Conclusion

Artificial intelligence offers Africa a unique opportunity to address some of the structural weaknesses in its health systems by improving access, quality and responsiveness of care, even in the most constrained contexts. From Dakar to Casablanca, via Lagos and Accra, initiatives are multiplying and proving that innovation can be a powerful lever for health equity.
To turn innovation into real impact, the barriers must be removed: lack of infrastructure, regulatory gaps, weak cybersecurity and cultural resistance still slow the integration of AI into public-health policy.

From now on, the question is no longer whether AI can transform health in Africa, but how to build an ethical, sovereign and inclusive framework so that this revolution benefits everyone, and who will carry that ambition forward.