Vice President, Internet of Things Group
General Manager, Health, Life Sciences and Emerging Technologies
By Stacey Shulman
I’ve spent much of my career in the retail and innovation space, helping retailers including Levi’s and American Apparel understand and deploy cutting-edge technology throughout their stores. I’ve helped them use technology to help streamline costs while providing the best customer experience, like with RFID tags that allow store associates to quickly find lost inventory. Since the pandemic’s onset, we’ve seen retailers innovate quickly and incorporate technology to protect their employees’ safety and provide alternative shopping methods for consumers.
But retail isn’t the only industry that’s ripe for disruption. The pandemic has pushed us as a society to look for ways to move faster across industries and technologies and has accelerated the pace of technological development and adoption.
Artificial intelligence (AI) in health and life sciences has greatly accelerated. From helping clinicians develop personalized protocols to streamlining clinical workloads or unlocking insights in genomics, infusing AI into these industries may be much closer than many initially thought. A July 2020 Intel survey of U.S. healthcare leaders found that 84% surveyed have already deployed or expect to deploy AI in their clinical workflow. This is an increase from 37% in 2018.
But while the promise of AI in healthcare is profound for improved patient care, significant industry barriers remain – namely trust and cost.
The good news is that trust in AI is growing: 67% said they were less than two years away from trusting AI to process medical records, compared with 54% in 2018. Similarly, 62% agreed that we are less than two years from trusting AI to analyze diagnostics or screenings, compared with 40% in 2018.
Overwhelmingly, healthcare leaders agree that the clinical value of AI in supporting physicians is clear:
- 94% agree that it will help provide clinicians with prediction analytics for early intervention.
- 92% agree that it will be used in clinical decision support.
- 92% agree that it will enable multiple specialists to collaborate or improve patient care.
While there are concerns around the costs associated with deploying AI, a recent Accenture analysis found that there are also great savings to be had. For example, AI can reduce the time doctors and nurses spend on administrative tasks, including filling out health records. It can also help physicians spend more time with expectant mothers through automated obstetric measurements. And AI can help medical staff triage potentially life-threatening cases faster, while increasing physician productivity and enhancing patient care. In all of these examples, we worked with the healthcare companies to build and optimize AI into their existing solutions, helping to speed up deployment while removing the need to buy costly new hardware.
Still, challenges will not disappear overnight.
While the pandemic is accelerating AI healthcare adoption out of necessity, we must continue to work collaboratively, utilizing public-private partnerships and emerging technology solutions to make solutions more accessible and trusted.
It’s time AI in healthcare had its shining moment, helping the industry to revolutionize our collective health outcomes.
Stacey Shulman is vice president in the Internet of Things Group and general manager of Health, Life Sciences and Emerging Technologies at Intel Corporation.