10 Promising AI Applications in Health Care

10 Promising AI Applications in Health Care

Brian KalisMatt CollierRichard Fu

MAY 10, 2018

There’s a lot of excitement right now about how artificial intelligence (AI) is going to change health care. And many AI technologies are cropping up to help people streamline administrative and clinical health care processes. According to venture capital firm Rock Health, 121 health AI and machine learning companies raised $2.7 billion in 206 deals between 2011 and 2017.

PETER DAZELEY/GETTY IMAGES

The field of health AI is seemingly wide—covering wellness to diagnostics to operational technologies—but it is also narrow in that health AI applications typically perform just a single task. We investigated the value of 10 promising AI applications and found that they could create up to $150 billion in annual savings for U.S. health care by 2026.

We identified these specific AI applications based on how likely adoption was and what potential exists for annual savings. We found AI currently creates the most value in helping frontline clinicians be more productive and in making back-end processes more efficient—but not yet in making clinical decisions or improving clinical outcomes. Clinical applications are still rare.

There’s a lot of excitement right now about how artificial intelligence (AI) is going to change health care. And many AI technologies are cropping up to help people streamline administrative and clinical health care processes. According to venture capital firm Rock Health, 121 health AI and machine learning companies raised $2.7 billion in 206 deals between 2011 and 2017.

PETER DAZELEY/GETTY IMAGES

The field of health AI is seemingly wide—covering wellness to diagnostics to operational technologies—but it is also narrow in that health AI applications typically perform just a single task. We investigated the value of 10 promising AI applications and found that they could create up to $150 billion in annual savings for U.S. health care by 2026.

We identified these specific AI applications based on how likely adoption was and what potential exists for annual savings. We found AI currently creates the most value in helping frontline clinicians be more productive and in making back-end processes more efficient—but not yet in making clinical decisions or improving clinical outcomes. Clinical applications are still rare.

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https://hbr.org/2018/05/10-promising-ai-applications-in-health-care

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