Barriers and opportunities for research in artificial intelligence applied to health in Latin America: A perspective based on SWOT analysis

Abstract

Artificial intelligence (AI) has progressively consolidated as a tool with the potential to transform health research and clinical practice, particularly in settings characterized by high care demand and limited resources. In Latin America, the incorporation of these technologies occurs within a context marked by a high burden of disease, deep structural inequalities, fragmentation of health systems, and notable institutional heterogeneity, factors that directly shape the development, validation, and implementation of AI-based solutions. This article presents a reflection based on expert consensus on the main barriers and opportunities for research in artificial intelligence applied to health in the region. The document was developed through a structured deliberative process involving specialists in hepatology, surgery, and AI from different countries in Latin America and Europe, using SWOT analysis as the conceptual framework to organize the discussion. This exercise made it possible to identify relevant weaknesses, including the limited availability of leadership with formal training in AI, the fragility of collaborative research networks, insufficient dedicated funding, and persistent gaps in technological infrastructure. In parallel, important opportunities were recognized, such as the growing interest of the academic and clinical community, the availability of national a international funding calls the potential to consolidate multidisciplinary teams, and the support of scientific societies and regional and international collaborative networks. Based on these elements, strategies are proposed to strengthen regional capacities through structured training programs collaborative projects focused on priority clinical problems, sustainability-oriented research models, and the development of ethical and regulatory frameworks aligned with the Latin American context. Finally, the contrast with the European experience underscores the need to advance toward integrated ecosystems in which research, clinical practice, and regulation evolve in a coordinated manner, as a prerequisite for the responsible and sustainable adoption of AI in health. This consensus proposes an initial roadmap to guide the responsible development of AI research in health in Latin America.