{"@context":"https://schema.org","@type":"ScholarlyArticle","headline":"Insights Into the Current and Future State of AI Adoption Within Health Systems in Southeast Asia: Cross-Sectional Qualitative Study.","author":[{"@type":"Person","name":"Mochammad Fadjar Wibowo"},{"@type":"Person","name":"Alexandra Pyle"},{"@type":"Person","name":"Emma Lim"},{"@type":"Person","name":"Joshua W Ohde"},{"@type":"Person","name":"Nan Liu"},{"@type":"Person","name":"Jonas Karlström"}],"datePublished":"2025","isPartOf":{"@type":"Periodical","name":"Journal of medical Internet research"},"identifier":"https://doi.org/10.2196/71591","description":"\n Background\n Artificial intelligence (AI) holds potential to enhance health systems worldwide. However, its implementation in health systems in Southeast Asia (SEA)—a region of diverse geopolitical and socioeconomic development—has been understudied.\n \n \n Objective\n This study aims to gain insights into the current state and future prospects of AI technology from participants most directly involved in its adoption across health systems in SEA whose perspectives have received limited attention in research to date.\n \n \n Methods\n We used a cross-sectional qualitative research design. Data were collected through 31 semistructured interviews with participants working in or significantly involved with the implementation of AI-enabled technologies within health systems across 7 SEA countries: Brunei Darussalam, Indonesia, Myanmar, Singapore, Thailand, Vietnam, and the Philippines. The participants represented the public, private, and nonprofit sectors. They included innovators, health care professionals using AI, professionals from nongovernmental and multilateral organizations, corporate professionals, academics, policy makers, regulators, and investors. All interviews were audio recorded and transcribed verbatim. The collected data were then analyzed using thematic analysis methodology to identify key themes.\n \n \n Results\n Of the 31 participants, 8 (26%) were from lower–middle-income countries, 16 (52%) from upper–middle-income countries, and 7 (22%) from high-income countries. Through thematic analysis, five major categories emerged: (1) AI technology acceptance, (2) disparities in digital transformation, (3) technology governance, (4) data governance, and (5) AI for health system transformation. Participants discussed the promise of AI technology for adoption and integration in the health sector. In lower–middle-income and upper–middle-income countries, disparities in digital transformation—such as infrastructure barriers, market access concerns, and limited investment—were viewed as critical impediments. Across all country income levels, technology and data governance were considered essential for the ethical integration of AI into health care systems. AI is perceived to have the potential to transform health systems, including population health management, service accessibility, operations management, health systems financing and health care payment, and personalized medicine.\n \n \n Conclusions\n Our study provides novel perspectives and valuable insights into the current state and future prospects of AI adoption across health systems in SEA. By capturing the experiences and opinions of a broad range of professionals involved in health care and AI, this research provides a nuanced understanding of the opportunities and hurdles associated with health AI in the region. For the full potential of AI-enabled technologies to be successfully implemented and ultimately contribute to the transformation of health systems in the region, foundational investments are needed in digital infrastructure, technology governance, and data governance. These fundamental pillars are crucial for fostering an environment in which AI can be effectively and ethically leveraged to improve health outcomes and strengthen health care systems throughout SEA.\n ","url":"https://innscience.ca/es/community/literature/d251ae83-b5ee-4195-b683-5a4458ad641f"}