Generative AI in healthcare: Adoption trends and what’s next

| Article

The transformative power of generative AI (gen AI) will likely reshape the healthcare industry over time, and organizations are beginning to take action. In our Q1 2024 survey, more than 70 percent of respondents from healthcare organizations—including payers, providers, and healthcare services and technology (HST) groups—say that they are pursuing or have already implemented gen AI capabilities (see sidebar, “Research methodology”).

The Q1 2024 survey, which included 100 US healthcare leaders, was conducted in March and comes after the Q4 2023 survey of 100 US leaders, which was conducted in December 2023. As we look at the responses across these populations in both surveys, a few themes emerge.

Integration and intentions

Most respondents say their healthcare organizations are at least pursuing generative AI proofs of concept, if not already implementing the technology.

Partner or pioneer

Surveyed organizations that are already implementing gen AI capabilities do so primarily through cobuilding partnerships.

The ROI for gen AI

Among the respondents who reported implementing gen AI, few have quantified its impact, but nearly 60 percent believe it yields a positive ROI.

Gen AI’s vast scope

Gen AI is thought to hold the highest potential value in improving clinical productivity as well as patient engagement and experience.

Hurdles to scale up

Risk concerns and considerations was the top challenge among healthcare organizations pursuing generative AI.

After gen AI entered the global stage at the end of 2022, we now see the healthcare industry more actively considering its strategy for using this technology. While these surveys are small and do not represent an exhaustive view of all healthcare stakeholders, they are meant to provide early insights into gen AI’s potential. As the survey results show, many healthcare leaders have begun pursuing plans to more broadly adopt the technology, which has in part been enabled by strategic partnerships. Given the complexities regarding technical implementation and integration across a business, cross-functional collaborations allow organizations to bring in outside talent while taking advantage of building flexible and customizable gen AI solutions, compared with buying off-the-shelf solutions. Yet depending on an organization’s tech maturity or how straightforward a use case is, buying publicly available gen AI products may offer a viable alternative to tap into the technology’s value proposition. Direct purchases may make sense, particularly for functional uses that have matured faster, such as for customer service applications.

As gen AI deployment progresses, many surveyed leaders share that their organizations are focused on initially using this technology to support clinically adjacent applications, with clinical and administrative efficiency and patient/member engagement surfacing as areas believed to gain the most from gen AI. However, as organizations develop strong competencies in governance and risk management, we expect additional focus on core clinical applications as well, further improving the overall patient/member experience.

Despite gen AI’s promise, the path to responsible usage is not without its hurdles. Risks such as inaccurate outputs and biases are particularly critical in healthcare when dealing with patients. As organizations introduce this new technology into workflows, AI risks seem to be top of mind for many surveyed healthcare leaders. Risks will need to be proactively mitigated, which starts with a concerted focus on establishing governance processes, frameworks, and guardrails to anticipate, identify, and manage risks. By doing so, healthcare organizations can use gen AI to help ensure that benefits are realized in line with regulatory expectations without compromising ethics or safety.

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