A new World Economic Forum report released today highlights the transformative potential of artificial intelligence (AI) in healthcare and the importance of public-private collaboration in driving its global adoption.
Scaling Smart Solutions with AI in Health: Unlocking Impact on High-Potential Use Cases - developed in collaboration with global management consulting and technology firm ZS - aims to spur public-private collaboration to accelerate the responsible application of AI in healthcare. In response to the systemic challenges that are straining health systems worldwide, the report proposes a global taxonomy for healthcare AI uses and shows how global healthcare systems could unlock the full potential of these new technologies to transform patient care, reduce costs and enable people to live healthier, longer lives.
"We are at a critical juncture in global health and healthcare, as mounting headwinds threaten collective wellness as well as employers, economies, budgets and societal resilience," said Shyam Bishen, Head of the Centre for Health and Healthcare and Member of the Executive Committee at World Economic Forum. "Closely governed advancements in AI are critical to supporting a broader digital and data-driven transition to intelligent healthcare systems, which can meet populations' needs and transform healthcare outcomes, access, and efficiency."
"The question is no longer whether the technology exists for AI to transform healthcare. It does," added ZS Chief Executive Officer Pratap Khedkar. "The question is whether or not stakeholders can pull together to set the conditions for its widespread use and adoption. If adopted broadly and responsibly, AI holds the potential to radically transform healthcare systems and improve health outcomes for all."
The new report - led by the Forum's Centre for Health and Healthcare - is the result of a comprehensive analysis of more than 400 existing AI use cases as well as in-depth interviews with 50 global leaders across technology, healthcare delivery, biopharma, government, academia and more.
Among its key findings, the report shows how AI offers the potential to diagnose a range of diseases at scale, leading to early interventions for individuals at greater risk, as well as counter infectious diseases through AI-powered systems that can predict future outbreaks, map their spread and deliver customized mitigation strategies to reduce their impact. Clinical trials can be enhanced by facilitating optimal site selection, participant recruitment and the creation of more representative synthetic data.
While the report highlights the potential of AI in healthcare, it also identifies common barriers to its adoption. These barriers include insufficient high-quality data, low trust in AI solutions and inadequate technological infrastructure, among others.
Public-private support for creating a strong data foundation and improved privacy laws, responsible and transparent design of AI algorithms, and significant investment to adopt these technologies at scale will be crucial to overcome these barriers and ensure equitable access to these innovations worldwide. (ANI/WAM)
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