Infrastructure gaps stall APAC healthcare AI rollout

China, South Korea, and Taiwan are positioned to record the strongest uptake over the medium term.

Artificial intelligence (AI) adoption across Asia-Pacific's (APAC) healthcare sector will expand as governments embed the technology into national health strategies, but gaps in infrastructure, data, and regulation will slow the shift to system-wide deployment.

BMI said in a report that the strongest uptake will come from markets that combine public investment in AI with mature digital health ecosystems and clear policy support.

The firm expects Mainland China, South Korea, and Taiwan to see the strongest uptake, with China predicted to emerge as a regional leader over the medium term.

"AI deployment in healthcare across APAC will strengthen over the medium term as governments increasingly embed the technology within broader health transformation strategies," it said.

Taiwan's Ten AI Initiatives Promotion Plan, approved in January 2026, includes healthcare under smart applications and AI robotics, alongside interoperable electronic medical records, AI-supported chronic disease management, and expanded national health data infrastructure.

South Korea's 2026-2030 AI Welfare and Care Innovation Plan, announced by the Ministry of Health and Welfare in February, outlines the expansion of AI in welfare, elderly care, and long-term care services.

Singapore also refreshed its National AI Strategy in May, naming healthcare as one of four sectors for National AI Missions.

The city-state is also scaling generative AI for clinical documentation and imaging and plans to consolidate public healthcare apps under an enhanced HealthHub platform by November 2026.

Mainland China issued a framework for the standardised application and innovative development of intelligent agents in May, identifying healthcare as a priority sector for deployment and oversight.

Other markets—including Australia, Japan, and several Southeast Asian economies—are also positioned to expand healthcare AI use because of their established healthcare systems and digital infrastructure.

BMI expects adoption to remain more limited in lower-income and less digitally mature markets—such as Cambodia and Laos—where gaps in health IT infrastructure, electronic medical record uptake, and regulatory frameworks could constrain deployment.

"Uptake across APAC will remain uneven in the medium term as implementation challenges slow the transition to system-wide adoption," the firm said.

Healthcare providers face challenges integrating AI into clinical workflows, reimbursement systems, and legacy health IT infrastructure, it noted.

Fragmented data environments and limited interoperability also remain barriers, whilst digital maturity varies between urban tertiary hospitals and lower-level healthcare facilities.

“Governance will also become a more important bottleneck as AI moves closer to diagnosis, triage, risk prediction, and care planning, requiring clearer rules around clinical accountability, data privacy, cybersecurity, and model validation,” BMI said.

BMI said Singapore's focus on human oversight and governance shows that advanced markets will also take a cautious approach to healthcare AI deployment.

It added that the strongest near-term commercial opportunities will be in markets where infrastructure, governance, and public-sector procurement can support scaled implementation.