What Is the Current Status of GAI Adoption By Healthcare?
McKinsey & Company recently took a survey to get a feel for the state of GAI adoption in healthcare. Their “check-up” yielded some interesting results.
Generative AI (GAI) has come on the scene like a whirlwind. Can you believe that only two years ago, few people even heard of ChatGPT? Businesses in all industries are scrambling to see how ChatGPT and dozens of other GAI tools like it can improve productivity and give them a leg up on their competition.
As we have mentioned many times on these pages, if there was any industry that seemed tailor-made for the benefits that could be delivered by GAI, it is healthcare. But at the same time, due to privacy issues, integration with legacy systems and a host of other concerns, it is also the industry that faces the greatest challenges to large-scale GAI adoption. Such challenges have caused the healthcare industry to lag behind many others when it comes to GAI acceptance and implementation.
With all that in mind, global market analytics firm McKinsey & Company took a survey to get a feel for the state of GAI adoption in healthcare. Like a medical exam, their “check-up” yielded some interesting results.
McKinsey took healthcare’s pulse at two points in time—the fourth quarter of 2023 for baseline and the first quarter of 2024 for trend detection. The firm surveyed 100 representative U.S. healthcare leaders for each.
In a report on the project released last week, McKinsey analysts lay out five sets of results and observations. Here are the top five excerpts.
1. Most healthcare organizations are at least pursuing GAI proofs of concept.
In Q4 2023, 25% of respondents said they had already implemented gen AI. The count grew to 29% as of Q1 2024.
“Despite U.S. healthcare’s general interest in using AI, a substantial portion of respondents are still operating without any plans to pursue gen AI or still maintaining a wait-and-see approach.”
2. Healthcare organizations that are already implementing GAI do so primarily through building partnerships.
McKinsey’s Q1 2023 survey found 59 of 100 orgs partnering with third-party vendors to develop customized solutions. That number dropped to 42 by Q1 2024, but the count of orgs procuring GAI products that require limited customization swelled from 17 to 41.
“Among those who haven’t yet implemented gen AI, 41% say they intend to buy gen AI products. This behavior may be driven by this population’s concerns with risk (57% are not pursuing gen AI because of risk considerations) and technology needs (29%).”
3. Among early GAI implementers, few have quantified the technology’s impact.
However, 58% believe it is producing a positive ROI.
“As with any investment, it’s critical for stakeholders to be able to realize the value that gen AI promises. A measurable positive impact serves as strong reinforcement for continued and expanded use and investment.”
4. Surveyed healthcare leaders believe GAI’s greatest value will come on two fronts.
By name, the two are: “boosted clinical productivity” and “patient engagement.”
“Expectations are also high around gen AI’s potential to improve administrative efficiency and care quality.”
5. The No. 1 challenge for healthcare organizations pursuing GAI is risk.
Not far behind are insufficient capability, data and tech infrastructure, and proof of value.
“This demonstrates healthcare organizations’ limited tech readiness to deploy gen AI solutions and also to validate its capabilities.”
The report’s authors comment that, as GAI deployment progresses, healthcare organizations will likely focus on using the technology to support more “clinically adjacent” applications.
You can read the full report by following this link.
How BigRio Helps Bring LLM and Advanced AI Solutions to Healthcare
It’s interesting that two out of the top five concerns reported by the healthcare professionals that McKinsey surveyed had to do with trust and lack of customization as stumbling blocks to GAI implementation.
Such concerns were echoed in a recent report produced by the AMA that pointed out the many challenges that remain before the medical industry can embrace GAI on a major scale. Most of the concerns the AMA identified are a problem when healthcare organizations and clinicians turn to “commercial off the shelf” GAI solutions such as those created by big tech companies like Google, Microsoft, or OpenAI.
But what if you could surmount privacy, bias, and other challenges by building a GAI-LLM model for your healthcare organization’s unique targets and needs? You can, with BigRio’s Help!
BigRio has long been a facilitator and incubator in leveraging AI to improve healthcare delivery, originally in the field of diagnostics and research. We have recently been focusing our efforts on supporting startups and developing our own solutions that use LLMs and GAI to improve those areas of healthcare as well as in direct patient interactions, customer relationship management, EMR integration and so much more.
We are proud to have recently launched our proprietary LLM-driven tool, Odyssey Accelerator. It is a first-of-its-kind solution that enables businesses of all sizes who want to use GAI to transform the way they search or query enterprise data, design workflows, derive enterprise analytics, report generation, dashboards, and more, to build a proof of concept before scaling it enterprise-wide.
And, BigRio offers Generative AI Workshops for Accelerating Innovation in Healthcare with Generative AI. These are Customized Onsite, In-Person, Healthcare-focused, Learning & Ideation Workshops designed to Accelerate Your GenAI Journey.
We believe that Generative AI will be most powerful when it is used to enhance, not substitute, human knowledge and creativity.
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You can read much more about how AI is redefining healthcare delivery and drug discovery in my book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint.
