Mapping the Responsible Adoption of Artificial Intelligence for Global Health in Low Resource Settings: Scoping Review

This research project is a scoping review that seeks to map and synthesize evidence on the application of responsible artificial intelligence (AI) principles in health interventions implemented in low- and lower-middle–income countries (LLMICs). While AI has significant potential to address persistent challenges in global health systems, such as workforce shortages, weak infrastructure, and fragmented care, its adoption in resource-limited settings must be guided by principles of equity, inclusiveness, transparency, accountability, human rights, and contextual relevance. To date, evidence on responsible AI in these contexts remains fragmented, with no comprehensive review of how such principles are applied across the full lifecycle of AI interventions, from design and development to implementation and evaluation. Using the JBI Manual for Evidence Synthesis (2024) and following PRISMA-ScR reporting standards, the review will systematically search peer-reviewed databases (Medline Ovid, Embase, Web of Science), grey literature repositories (e.g., ProQuest Dissertations & Theses, WHO Global Index Medicus, Google Scholar), and the reference lists of relevant studies for all resources published up to August 28, 2025. No language restrictions will be applied, and non-English studies will be translated. Two reviewers will independently screen and extract data, focusing on bibliographic details, populations, intervention characteristics, responsible AI components, outcomes, and contextual factors. Data will be analyzed using descriptive statistics and qualitative content analysis, and results will be presented through narrative synthesis and a PRISMA-ScR flow diagram. The expected outcomes of this work include a comprehensive evidence map of AI-based health interventions in LLMICs that integrate responsible AI principles, as well as an analysis of gaps and opportunities for future research and practice. By highlighting best practices and areas needing further attention, this study will inform researchers, policymakers, and implementers seeking to advance the responsible adoption of AI for global health. Findings will be disseminated through peer-reviewed publications, webinars, and international conferences on digital and global health.