China, South Korea and Taiwan are expected to record the strongest growth over the medium term.
The adoption of artificial intelligence (AI) across the healthcare sector in Asia Pacific (APAC) will expand as governments incorporate it into their national health strategies, but gaps in infrastructure, data, and regulation will slow the transition to system-wide adoption.
BMI said in the report that the greatest adoption will come from markets that combine public investment in AI with a mature digital health ecosystem and clear policy support.
The company expects penetration to be strongest in mainland China, South Korea and Taiwan, with China emerging as a regional leader in the medium term.
“AI adoption in healthcare across the Asia-Pacific region will strengthen in the medium term, as governments increasingly incorporate AI technologies into broader healthcare transformation strategies,” the report said.
Approved in January 2026, Taiwan’s 10-point AI initiative promotion plan includes smart applications and AI robotics in healthcare, as well as interoperable electronic medical records, AI-assisted chronic disease management, and expanding national health data infrastructure.
South Korea’s 2026-2030 AI Welfare and Nursing Care Innovation Plan, released 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 updated its National AI Strategy in May, naming healthcare as one of the four sectors of the National AI Mission.
The city-state is also expanding its generative AI for clinical documentation and imaging, and plans to integrate public health apps into its enhanced HealthHub platform by November 2026.
In May, mainland China announced a framework for standardized application and innovative development of intelligent agents, identifying healthcare as a priority area for implementation and monitoring.
Other markets, including Australia, Japan, and several Southeast Asian countries, are also positioned to expand the use of medical AI due to their established healthcare systems and digital infrastructure.
BMI expects adoption to remain even more limited in lower-income and less digitally mature markets, such as Cambodia and Laos, where gaps in health IT infrastructure, widespread adoption of electronic health records, and gaps in regulatory frameworks may constrain adoption.
“Uptake across APAC will remain uneven in the medium term as implementation challenges slow the transition to system-wide adoption,” the company said.
Healthcare providers face challenges integrating AI into clinical workflows, reimbursement systems, and traditional health IT infrastructure, the report said.
Fragmented data environments and limited interoperability also remain barriers, but urban tertiary hospitals and lower-level healthcare facilities differ in their digital maturity.
“As AI moves closer to diagnosis, triage, risk prediction, and care planning, governance will also become a more important bottleneck, requiring clearer rules around clinical responsibility, data privacy, cybersecurity, and model validation,” BMI said.
BMI said Singapore’s focus on human oversight and governance shows that developed markets will also take a cautious approach to healthcare AI adoption.
It added that the strongest commercial opportunities in the near term are in markets where infrastructure, governance and public sector procurement can support large-scale implementation.
