The healthcare sector, like many others, has not been immune to the technological shift brought T about by artificial intelligence (AI). Touted as a great tool to aid in streamlining operations, AI and generative AI are predicted to contribute to around $100 billion in savings for the already burdened healthcare sector.
Yet, the applications and potential of the technology expand beyond just enhancing efficiency for day-to-day workplace tasks: it has also shown great promise in reducing barriers to access for healthcare knowledge and for supporting the complex analysis of data in drug trials and research. Al's data processing capabilities, while not unexpected, are precisely what is needed when we look to democratise healthcare and focus on an equitable future in healthcare.
The Asian Context
Historically, in Asia, the healthcare sector is one where social and economic disparity is placed under a microscope. Around 1.6 billion people in Asia and the Pacific lack effective access to social health protection due to a variety of legal and systemic issues.
Infrastructure issues in less developed economies means that local healthcare centres and systems are simply unable to accommodate patients in need. Even if private healthcare options exist for some conditions, many patients may not have access to treatments or care.
According to OECD data, the number of health resources and personnel available to populations across the APAC region is highly dependent on the number of resources allocated to the sector as well as population growth rates and density.
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