A new report has revealed that 85% of healthcare organisations are developing their own AI in-house, with generative artificial intelligence (genAI) applications being the most commonly applied.
碍笔惭骋鈥檚 surveyed 183 senior healthcare leaders from mid-to large-sized healthcare systems across eight countries, including the US, UK, Japan, and Germany.
AI鈥檚 top three applications in healthcare were genAI, speech recognition, and agentic AI 鈥� an emergent form of AI considered to be the next evolution of genAI.
础听聽on AI in healthcare by GlobalData forecasts that global revenue for AI platforms across the sector will reach a valuation of almost $19bn by 2027. In particular, the radiology field experienced some of the highest implementation of AI technologies, with genAI serving to streamline processes in the field and account for global physician shortages.
Meanwhile, a respective 59% and 72% said AI had been systematically incorporated into their service and product development and that their organisations had achieved appreciable efficiency-related improvements by adopting the technology.
Infrastructurally, a respective 69% and 84% reported that they are using cloud-based platforms or data platforms with AI capabilities.
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By GlobalDataThe survey also reflects a clear sentiment that AI investment is important when looking ahead. In comparison to 86% expressing the belief that AI adoption would give their organisation a competitive edge over those who did not, 85% said they were investing in AI for exploratory projects that would not have an immediate return on investment (ROI).
Challenges
While AI鈥檚 adoption in healthcare is pronounced, respondents to 碍笔惭骋鈥檚 survey also highlighted several challenges. 84% said they had faced operational challenges when implementing AI such as data issues, a lack of skills, and legal issues.
However, 77% reported that they are increasing their investment in AI to manage the highlighted issues. In addition, 69% of respondents said they felt pressurised to demonstrate ROI from their AI adoption, implying that some may have invested in the technology without a clear rationale around getting the most out of it, potentially putting their investments at odds with stakeholders.
碍笔惭骋鈥檚 proposition
Alongside its findings, KPMG outlined a strategy for healthcare organisations when embarking on an AI transformation.
The proposed measures include the formulation of a clear AI strategy that has in mind clear aims such as improving patient outcomes, workforce experiences, population health, and reducing overall costs by adopting the technology.
Other infrastructural guidelines suggested by KPMG include the advice that healthcare organisations create sustainable technology and data infrastructure by modernising legacy systems and investing in secure, interoperable platforms, and build trust through transparent AI practices, ethical governance, and investing in robust cybersecurity protocols.
KPMG’s global healthcare head Dr Anna van Poucke commented: 鈥淎I has the potential to fundamentally reshape healthcare 鈥� not by replacing the human touch, but by enhancing it.
鈥淏y integrating AI across different clinical and community settings and different operational streams, we can improve outcomes, ease the burden on healthcare workers, and create more resilient, patient-centred health systems.鈥�
