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February 22, 2026

ADB approves $950,000 for AI health projects in Pakistan, Bangladesh, Indonesia

Technical assistance to assess AI in diagnosis, treatment, management and build governance roadmaps

Monitoring Report

Monitoring Report

February 22, 2026

ADB approves $950,000 for AI health projects in Pakistan, Bangladesh, Indonesia

The Asian Development Bank (ADB) will provide $950,000 in regional technical assistance to Pakistan, Bangladesh and Indonesia to boost the adoption of artificial intelligence (AI) in healthcare.

The programme will assess AI applications in health promotion, screening, diagnosis and treatment and develop roadmaps for AI adoption. It will also support countries in designing AI governance frameworks, including validation, data privacy safeguards, mitigation of algorithmic bias, and post-market monitoring.

The assistance targets three AI categories. Clinical AI includes AI-assisted point-of-care diagnosis and treatment using image processing and pattern recognition. Healthcare management AI helps hospitals manage appointments, consultations, prescriptions and follow-ups, automate administrative tasks, improve patient flow and reduce health worker burnout. Generative AI and AI agents will support telemedicine, medical education and distance learning in underserved areas.

ADB said AI could transform health service delivery, improve efficiency, quality and equitable access. Big data analytics, deep learning, natural language processing and robotics could enhance diagnostics, treatment, health management, drug discovery and personalised medicine. Administrative processes such as record-keeping and claims monitoring may also be automated.

The programme will survey available AI tools, provide technical guidance, and help member countries build domestic AI ecosystems covering research, technology transfer, commercialisation and procurement.

ADB noted that geopolitical tensions, economic uncertainty, and shifts in global health aid have constrained health investments. Member countries face gaps in infrastructure, equipment bottlenecks, uneven distribution of skilled health workers, insufficient training budgets, rising healthcare costs, and fragmented digital health systems.

 

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