Revolutionizing African Healthcare: A Systematic Review of Artificial Intelligence and Data Governance

Background: African health care Systems are confronted by continuing infrastructure disparities or lack of capacity about the workforce and unequal access to care. To address these challenges, artificial intelligence (AI) and data governance frameworks have become the change makers in the health sector, especially in the wake of the African Union Convention on Cyber Security and Personal Data Protection (2014) which was used to provide the foundation upon which digital innovators look to bring solutions to life in the healthcare sector. Purpose: This study investigates the integration of AI in African healthcare systems post-2014. It examines the role of AI in disease detection, patient management and other health outcome, ethical standards and policy development implications. Methods: A total of 41 peer-reviewed articles published in the years between 2015 and 2023 were analysed by means of a systematic review of the literature. PubMed, IEEE Xplore, and Google Scholar were used as the sources. Search terms included “AI in healthcare,” “data governance” and “Africa,”. Also, the review has included the grey literature which did not follow the PRISMA guidelines. Empirical evidence of implementation of AI across African countries in the healthcare contexts was the basis of the studies selected. Results: The number of publications related to healthcare via AI has increased by 35% in 2022-2023 colocation with increasing interest and investment in this issue. It was found out that AI: contributes to significant parts of diagnostic accuracy, operational efficiency and predictive analytics in several medical disciplines. Despite these critical challenges, there remain two major sticking points regarding infrastructure, regulatory enforcement, and usage of patient data in the ethical way. Conclusions: The study indicates the need for the immediate development of targeted interventions by the African governments, health ministries, research institutions, and digital health stakeholders. With these include the establishment of robust governance mechanism, ethical oversight frameworks and digital infrastructure as investment. In the future, it is suggested that longitudinal study and cross regional policy comparison should be conducted to provide sufficient support for sustainability of AI integration in healthcare systems.