Towards Responsible Artificial Intelligence (AI): An Analysis of AI Policies in Selected Low- and Middle-Income Countries

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ID: 333678
2026
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Abstract
Abstract Introduction: This study examines artificial intelligence (AI) policies in low- and middle-income countries (LMICs) and their implications for health systems and public health. Methods: We searched and reviewed 59 official AI-related policies from 27 Asian and African LMICs issued up to December 2025. An inductive codebook was developed to analyze policy patterns. Results: Policy development has accelerated since 2020, yet healthcare-specific AI regulation remains rare, with most policy documents emphasizing the general AI governance. Across regions, policies consistently prioritize data, ethics, institutional frameworks, infrastructure, and workforce development, while monitoring, environmental sustainability, and sector-specific regulation receive limited attention. African policies more often address workforce displacement, foreign investment, and environmental sustainability, whereas Asian policies emphasize domestic resource mobilization and skills development. Investment commitments are rarely linked to measurable health system outcomes. Conclusions: Overall, the primary health governance gap lies not in the absence of responsible AI principles, but in their limited translation into sector-specific operational requirements. Cross-sectoral governance should therefore be complemented by health-specific requirements for clinical validation, human oversight, accountability, and post-deployment monitoring.
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openalex_W7223340625 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jinyou Sheng, Shrihaan Chaudhary, Lisa Bourget, Katherine Robsky, Krishna Udayakumar, Wenhui Mao
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Journal Health Affairs Scholar
Year 2026
DOI
10.1093/haschl/qxag295
URL
https://doi.org/10.1093/haschl/qxag295
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