The Yuan requests your support! Our content will now be available free of charge for all registered subscribers, consistent with our mission to make AI a human commons accessible to all. We are therefore requesting donations from our readers so we may continue bringing you insightful reportage of this awesome technology that is sweeping the world. Donate now
Data, infrastructure barriers hamper AI's cure of Africa's healthcare woes
By Ahmed Zahlan  |  May 08, 2024
Data, infrastructure barriers hamper AI's cure of Africa's healthcare woes
Image courtesy of and under license from
Africa will gain the most from AI’s activation in healthcare, but the road to fulfilling this vision is a rocky one. Fulbright Scholar Ahmed Zahlan, who is pursuing his PhD in AI healthcare startups, charts the path the second most populous continent must take to reach this goal.

NEW YORK - The integration of artificial intelligence (AI) into healthcare is garnering great attention due to its transformation of medical practices and enhancement of patient care. Application of this groundbreaking technology faces distinct challenges within the healthcare systems of many African countries, however.
This article examines the specific obstacles African healthcare providers encounter in their efforts to seamlessly incorporate AI, with a focus on infrastructure deficiencies, the nature of data required for effective AI applications, and the position of African nations on the global AI readiness index. As the discussion progresses, it will quickly become evident that addressing each of these three main issues is crucial in fully deploying AI to improve Africa’s healthcare and ensure its equitable participation in the global advance of medical technology. 

Africa’s current infrastructure 

The healthcare infrastructure in most African countries presents a complex scenario marked by various difficulties that affect efforts at modernization - the smooth integration of AI among them. A lack of modern medical equipment and outdated information systems are significant technological barriers that hinder AI.1 Logistical issues also exacerbate this situation - vast distances, underdeveloped transport networks, and unreliable power supplies are all hindrances to efficient AI implementation.2

Resource constraints such as financial limitations and a scarcity of skilled personnel also erect substantial hurdles. The absence of comprehensive digital health records and interoperability standards makes it difficult - sometimes impossible - to share the data indispensable for AI algorithms that depend on diverse datasets.3 The need for robust internet connectivity and real-time data access means the di

The content herein is subject to copyright by The Yuan. All rights reserved. The content of the services is owned or licensed to The Yuan. Such content from The Yuan may be shared and reprinted but must clearly identify The Yuan as its original source. Content from a third-party copyright holder identified in the copyright notice contained in such third party’s content appearing in The Yuan must likewise be clearly labeled as such.
Continue reading
Sign up now to read this story for free.
- or -
Continue with Linkedin Continue with Google
Share your thoughts.
The Yuan wants to hear your voice. We welcome your on-topic commentary, critique, and expertise. All comments are moderated for civility.