Generative AI Will Transform Health Care Sooner Than You Think
Published in Artificial Intelligence.
Generative AI has quickly become a major factor in health care, but executives must understand how to use the technology in order to capitalize on its potential while avoiding the risks inherent in applying it to patient care. We analyzed generative AI use cases across different health segments, looking at both solutions already on the market and those likely to arrive soon.
Emerging generative AI use cases now exist in all health care segments, from providers and pharmaceutical firms to payers, medtech, service providers, and public health agencies.
Companies need to manage the potential risks of AI, including biased outputs, false results, abuse of patient privacy, and and overreliance among patients on AI-generated guidance.
To create the right foundation for generative AI, health care organizations should create an enterprise-wide strategy, build data systems, invest in capabilities, forge strategic partnerships, and integrate with the broader industry ecosystem.
Generative AI entails some clear uncertainties and risks, but it also holds the potential to dramatically increase efficiency, improve the quality of care, and create value for health care organizations. Leaders need to plot a path to capitalizing on the technology—starting today.
Generative AI has quickly become a major factor in a number of industries, including health care. It has the potential to transform the sector, but executives must understand how to use the technology in order to capitalize on its potential while avoiding the risks inherent in applying it to patient care. We analyzed numerous use cases across health segments, looking at both solutions already on the market and those likely to arrive soon. Our goal was to demystify generative AI and help leadership teams make sense of the options.
Generative AI algorithms can analyze large volumes of medical data and create entirely new content. The technology can improve the quality of care, make it more accessible and affordable, reduce inequities in research and care delivery, and help companies unlock value in new ways. Moreover, generative AI overcomes some of the previous hurdles to AI adoption in health care. It requires less data, is more adaptable to unfamiliar situations, and can interface better with clinical staff. These features make generative AI more broadly applicable and transferable to different health care tasks.