The Equity Impact of Digital Health and Artificial Intelligence Tools on Health Outcomes in Underserved Populations: A Narrative Review and Conceptual Model

Abstract

Digital health and artificial intelligence technologies such as telemedicine, mobile health applications, clinical decision support systems, and predictive analytics are rapidly transforming healthcare delivery across diverse global settings. Although these innovations offer substantial potential to improve efficiency, expand coverage, and enhance clinical outcomes, growing concern remains that they may unintentionally reinforce or worsen existing health inequities affecting underserved populations. Because digital and artificial intelligence health research spans multiple disciplines, this narrative review synthesizes evidence from global health, health equity frameworks, artificial intelligence ethics, and sociotechnical systems to examine how digital transformation shapes equitable health outcomes. The findings show that digital and artificial intelligence tools can improve access to healthcare services, reduce geographic and logistical barriers, and enhance diagnostic accuracy. However, these benefits are not evenly distributed. Persistent disparities related to digital connectivity, affordability, digital literacy, data representation, and algorithmic performance may result in exclusion or harm among marginalized groups. To systematically explain these patterns, this review introduces the Equity Pathways Model, which identifies three interconnected mechanisms through which digital health and artificial intelligence influence equity outcomes. The Access pathway explains how digital tools can reduce traditional barriers to care while simultaneously creating new forms of exclusion linked to technology access and digital skills. The Quality of Care pathway highlights how artificial intelligence systems may enhance clinical decision making but also produce biased or unreliable outcomes for underrepresented populations. The System Structural pathway emphasizes how governance arrangements, political economy, institutional capacity, and sociocultural context shape whether digital innovations mitigate or reinforce structural inequities. Together, these pathways provide a framework for distinguishing digital health and artificial intelligence interventions that enhance equity, those that have neutral effects, and those that exacerbate disparities. The review offers an international perspective and proposes equity by design principles to guide researchers, policymakers, and technology developers in ensuring that digital health and artificial intelligence innovations contribute to the advancement of global health equity, particularly in low resource and underserved settings.

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