Global Health Inequities and the Role of Agentic AI in Low-Income Settings: A Healthcare Management Perspective

Abstract

Global health inequities continue to restrict access to timely and quality care in low- income settings Which have limited infrastructure, workforce shortages, financial barriers & geographic disparities that remain persistent challenges. Emerging advancements in artificial intelligence, particularly agentic AI, offer new opportunities to strengthen healthcare delivery in the resource constrained environments. These systems can support in decision making, improve early diagnosis, and enhance service reach. This chapter adopts a narrative literature review and conceptual analysis. It synthesises the evidence from peer reviewed studies, global health reports, and the policy documents. The analysis examines applications of agentic AI in areas such as telehealth, disease surveillance, clinical support and the community based care. It also evaluates critical concerns including digital exclusion, algorithmic bias ,data privacy, and infrastructural limitations. The chapter argues that agentic the AI can help in reducing healthcare disparities when implemented within inclusive and ethically governed frameworks. It also highlights the need for context-sensitive design, local capacity development & the supportive policy environments. The study also provides the structured understanding of how AI-driven solutions can help in improving accessibility, efficiency and equity in the underserved populations.