Artificial intelligence (AI) is emerging as a transformative tool for improving health information delivery, particularly in developing countries where health systems face shortages of skilled personnel, fragmented data, limited infrastructure, and uneven access to specialist services. Health information is central to clinical decision-making, disease surveillance, health planning, resource allocation, and progress towards universal health coverage. Yet, in many resource-constrained environments, information systems remain dependent on paper-based records, delayed reporting, incomplete datasets, and weak interoperability. AI offers opportunities to process volumes of information, identify patterns, support decision-making, and extend expertise beyond urban centres.
AI is reshaping how health information is generated, interpreted, and delivered, with particular relevance for health systems under strain. In African and other low-resource settings, AI’s value lies less in technological novelty than in its capacity to strengthen the core functions of health information systems - data quality, timeliness, and actionable insight, when deployed with discipline and contextual fit. Its effectiveness cannot be separated from the realities of health systems. This article therefore examines the opportunities, challenges, and prospects of using AI to strengthen timely, equitable, reliable, and health information delivery in developing and resource-constrained settings.
OPPORTUNITIES: AUGMENTING SCARCE CAPACITY
AI can extend the reach of limited human resources by automating routine analytic tasks and supporting frontline decision-making. Machine-learning models for image interpretation, for example, have demonstrated diagnostic accuracy of 92–98% in radiology applications, offering a way to mitigate specialist shortages in remote facilities. In Tanzania, early deployments of generative AI tools such as ChatGPT were perceived by clinicians as useful for enhancing decision support and patient counselling, despite infrastructural constraints. Outbreak prediction and disease-surveillance systems powered by AI have shown promise in identifying anomalies in routine data streams, enabling faster public-health responses where traditional reporting lags by weeks, and even by months.
CHALLENGES: INFRASTRUCTURE, DATA, AND GOVERNANCE
The translation of AI from pilot to scale remains constrained by foundational weaknesses. Over half of AI implementations face interoperability limitations, and 73% of low-resource health systems lack the enabling infrastructure especially reliable electricity, steady internet connectivity, and digital records; which are required for sustained operation. In sub-Saharan Africa, data scarcity, fragmented collection methods, and continued reliance on paper records impede the training and validation of locally relevant models. Ethical and regulatory gaps compound these challenges as only 27% of countries have established AI governance frameworks, raising risks of algorithmic bias, data-privacy violations, and erosion of trust. Workforce concerns are also salient; while 58% of health workers view AI as supportive, 43% fear job displacement, underscoring the need for change-management and skills development.
PROSPECTS: EMBEDDING ‘AI’ IN HEALTH-SYSTEMS STRENGTHENING
Sustainable impact depends on treating AI as a subsystem of broader health-information architecture, not a standalone solution. Equity-centred, nurse-led implementation frameworks emphasise contextual adaptation, local data governance, and integration with primary health care as preconditions for success. Investment priorities should focus on interoperable digital infrastructure, routine data digitisation, and capacity-building for health workers to interpret and oversee AI outputs. Where these foundations exist, AI can optimise resource allocation, standardise surveillance, and extend specialist expertise, thereby contributing to long-term development goals of universal health coverage (UHC) and resilient health systems.
Although AI has potential to strengthen health information delivery in developing countries and resource-constrained environments, its value will depend on how responsibly and realistically it is implemented. Gains are likely to come from using AI to augment health workers, improve data analysis, strengthen surveillance, support clinical decisions, and extend access to expertise rather than replace essential human capacities. Achieving these benefits requires investment in reliable electricity, connectivity, interoperable digital systems, data, cybersecurity, governance, and workforce skills. Emphasis must be placed on safeguards for privacy, transparency, accountability, equity, and public trust, particularly where regulatory frameworks remain underdeveloped. Therefore, AI should be embedded within broader health-system strengthening strategies and aligned with local priorities. With sustained investment, inclusive governance, and context-sensitive implementation, AI can become an important enabler of resilient health systems and universal health coverage.
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“Technological tools, including computers, search engines, statistical software, AI, and other digital applications routinely employed in contemporary scholarship, assisted in the preparation of this work. However, the conceptualization, analysis, interpretation, verification of information, conclusions, and responsibility for the content remain solely those of the author.” - Dr. Uzodinma Adirieje; CEO/Programmes Director, Afrihealth Optonet Association (AHOA), and President, African Refugees Council (ARC).
HIFA profile: Dr. Uzodinma Adirieje is a leading voice in health education, community health, and advocacy, with decades of experience advancing people-centered development across Africa and beyond. His approach to health education emphasizes participatory learning, knowledge transfer, and behavior change communication, ensuring that individuals and communities gain the skills and awareness to make informed decisions about their health. He develops and delivers innovative health promotion strategies tailored to local realities, particularly in resource-limited settings. In community health, Dr. Adirieje has championed integrated primary health care, preventive medicine, and grassroots health initiatives. Through Afrihealth Optonet Association (AHOA), which he leads, he connects civil society, community groups, and health institutions to strengthen healthcare delivery, tackle health inequities, and improve access to essential services for vulnerable populations. His work addresses infectious diseases, maternal and child health, nutrition, climate and health, environmental health, and emerging public health challenges. As a passionate advocate, Dr. Adirieje works with governments, NGOs, and international organizations to influence health policy, mobilize resources, and promote sustainable development goals (SDGs). He amplifies community voices, ensuring that health systems are inclusive, accountable, and responsive. His advocacy extends beyond health to governance, environment, and social justice, positioning him as a multidisciplinary leader shaping healthier and more equitable societies. afrepton AT gmail.com