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ISLAMABAD: The Asian Development Bank will provide technical assistance to Pakistan to enhance understanding and accelerate the deployment of artificial intelligence (AI) applications in health services.
The ADB has approved regional technical assistance amounting to $950,000 to help Pakistan, Bangladesh and Indonesia reap the benefits of AI for service excellence in health. The assistance will assess AI applications in health promotion, screening, diagnosis, and treatment, and will develop a roadmap for AI adoption.
The governments benefiting from the assistance have requested the ADB to help develop practical AI governance frameworks for anticipated AI innovations, including validation mechanisms, ways to safeguard data privacy and avoid algorithmic bias, and strategies for post-market performance monitoring. These countries are also keen to learn from best practices and use cases for AI tools in clinical care and health management.
In the past, the ADB had supported member countries investing in digital health, helping them adopt digital health information systems, establish common standards, and improve interoperability, thereby laying a strong foundation for big data analytics and AI applications. The assistance will provide timely support to enhance the AI readiness of member countries’ health systems through technical support and capacity building.
Bank’s project to assess AI applications in health promotion, screening, diagnosis and treatment
According to the project document, the assistance will focus on three types of AI applications that are relevant for ADB projects and are becoming mature. First, applications in the clinical context, including AI-assisted smart point-of-care diagnosis and treatment. Advances in image processing and pattern recognition allow medical equipment to become “smart” enough to generate highly accurate diagnoses at the point of care.
Second, AI applications in healthcare management aim to improve efficiency and the experience of both patients and health workers. Small hospitals can adopt AI solutions to provide a seamless experience for patients — from appointments, registration, consultations, prescriptions, and treatment to follow-ups — and to help manage patient flow. AI could also automate administrative tasks for health professionals and managers, freeing up time for patient care, improving doctor-patient interaction, and preventing burnout, which is common among health professionals in primary care and hospital settings.
Third, generative AI and AI agents could assist in distance learning, medical education, and telemedicine, providing clinical decision support for areas and populations with limited physical access. This could significantly improve the effectiveness and efficiency of medical education, upskilling of health workers, and public health education.
According to the project document, AI applications have the potential to transform health service organisation and delivery. They could improve the efficiency, quality, and equitable access to healthcare services. AI leveraging big data analytics, deep learning, natural language processing, and robotics could enhance health management, diagnostics, and treatment capabilities.
These technologies also open new possibilities in rapid drug discovery and personalised medicine. AI can automate record-keeping, claims monitoring, and other administrative tasks; reduce health worker burnout; and enhance efficiency, transparency, and quality of patient-doctor interactions.
The technical assistance will deliver knowledge to inform the design and implementation of ADB projects in Bangladesh, Indonesia and Pakistan. It will survey available AI tools in healthcare and help member countries develop roadmaps for home-grown AI ecosystems that integrate considerations for research and development, technology transfer, commercialization, and procurement.
The ADB notes that intensified geopolitics, economic uncertainties, and major shifts in the global health aid landscape have constrained the investments needed to improve health outcomes. Governments continue to face gaps in health infrastructure, equipment bottlenecks, mal-distribution of qualified health human resources, insufficient funding to upskill and incentivise health workers, escalating health expenditure, and the proliferation of fragmented and non-interoperable digital health applications.
Published in Dawn, February 22nd, 2026
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