Can artificial intelligence bridge the gaps for primary diabetes care in low-income and middle-income countries?

Artificial intelligence (AI) has the potential to improve primary diabetes care in low-income and middle-income countries (LMICs), where the rising burden of disease contrasts sharply with limited health-care resources. Emerging evidence shows the promise of AI for screening, risk prediction, monitoring, and personalised management of diabetes and its complications. However, substantial barriers remain, including infrastructure deficits, data fragmentation, equity and inclusivity challenges, limited prospective validation, and concerns about the acceptability, sustainability, and regulatory oversight of AI. The effective integration of AI into primary diabetes care will depend on coordinated investment in foundational infrastructure that includes large-scale development and rigorous validation of novel AI models for use by primary care physicians and patients across diverse populations. AI initiatives are also needed to support interdisciplinary and international collaborations spanning clinical, technical, and policy domains to ensure successful implementation. By aligning technological innovation with health care needs, AI could evolve from a proof-of-concept tool to a practical enabler of equitable, scalable, and cost-effective diabetes care in LMICs. In this Personal View, we outline the major opportunities and challenges of applying AI to primary diabetes care in LMICs, and propose directions for future development and implementation.