This article focuses on institutional and resource constraints that have held back innovation and the scaling up of Artificial Intelligence (AI) in many Low and Middle Income Countries (LMICs). Given the proper infrastructure, AI-driven interventions hold promising transformations for public health in resource-poor countries. The results confirm the potential of startups implementing AI in resource poor settings such as Asia and Africa. Additionally, it highlights several prerequisites to a robust healthcare system: clarity in policies and regulations, well-defined roles and responsibilities of government bodies, political stability, and high investment in primary healthcare. Data collected and literature review on AI companies in LMICs are widely published. To gain deeper insights on current challenges in adoption and implementation of AI, we interviewed healthcare startups in LMICs that have the potential for a global outreach.