Abstract
BACKGROUND: Artificial intelligence (AI) health applications developed in Global North countries are being diffused to the Global South but not without problems. OBJECTIVE: The goal of this integrative scoping review was to identify recent studies from 2022 to 2025 describing the contributions and challenges in using AI health applications in the Global South. METHODS: An integrative scoping review of 24 studies from seven databases identified four themes. MAJOR FINDINGS: This review adds to previous investigations by 1) focusing on data interoperability to resolve gaps in digitizing global health data required for accurate machine learning, 2) examining formidable economic and infrastructure hurdles for adoption and implementation of health AI in low-resource countries, 3) identifying barriers faced by emerging economies for partnerships with global AI biotech companies in AI health startups, and 4) calling for regulations and global surveillance of AI health applications. CONCLUSIONS: Practical implications for the future use of AI health applications in the Global South are discussed concluding that applications developed and trained on datasets from high income countries need to be recalibrated to work in the Global South. Additionally, due to the health-related disparities within the Global North the adoption of AI needs to be considered in its own context.