Over half of healthcare and life sciences organisations in Asia/Pacific are planning to have dedicated budgets for GenAI projects for timely investments, according to a recent IDC report, GenAI in Healthcare and Life Sciences: Current Trends and Future Potential in Asia/Pacific.
IDC expects Asia/Pacific to be the fastest-growing region in healthcare and life sciences GenAI spending.
This IDC report delves deeper into the current GenAI adoption trends, focus areas, organisational challenges, and preferred vendor attributes by healthcare and life sciences organisations in Asia/Pacific.
The report also provides a dashboard view of the use cases sourced from the IDC GenAI taxonomy report and maps these use cases with specific case studies by major healthcare providers and life sciences organisations from the region.
The report also features tech providers covered in the case studies by detailing their unique GenAI capabilities and offerings.
Other highlights of the report include:
* 77% of healthcare and 53% of life sciences organisations in Asia/Pacific are focusing on proofs of concepts (POCs) and use case identification for GenAI projects.
* Asia/Pacific will be the fastest growing region in healthcare GenAI spending, accounting for around 15% of the global spending by 2027.
* Regulatory risks and higher infrastructure costs are the topmost limiting factors for GenAI adoption in healthcare organisations.
* Robust data security capability and intuitive AI models are the topmost capabilities CIOs look for in a software provider to develop GenAI solutions.
“GenAI adoption in healthcare and life sciences, though at its nascent stage, is set to have a significant impact on enhancing clinician efficiency, improving workflow productivity, and hyperpersonalisation of patient experience,” says Manoj Vallikkat, senior research manager: health insights, Asia/Pacific at IDC.
“Currently, there is increased priority towards POCs as part of GenAI model deployments, this is set to transition to full-fledged deployments supported by matured clinical data sets, regulatory support, enhanced skill sets, and alignment of GenAI use cases with organisational priorities.”