Healthcare orgs eye optimization instead of innovation with generative AI

Generative AI (GenAI) has captivated the healthcare industry, with leading organizations expected to dump hundreds of billions of dollars into this category of AI-enabled tools over the next decade. 

With its ability to generate new content, including summaries of medical data, life-like communications, accurate computer code, and creative audio/visual assets, GenAI has a number of high-value applications across the operational, administrative, clinical, and patient experience arenas. 

These potential use cases range from the mundane (shortening check-in times and assisting with drafting emails) to the truly visionary (personalizing cancer therapies and developing semi-autonomous clinical agents), and if developed and deployed correctly, GenAI could help totally transform the way healthcare happens. 

But how much are organizations really interested in pushing the envelope with digital innovation and clinical discovery – or do they have less ambitious, more practical goals in mind? 

Recent industry data indicates a trend toward the latter. While there is enormous interest in adopting the latest and greatest GenAI techniques, organizations are largely looking toward use cases that fall on the less exciting side of the spectrum: the optimization of everyday processes to help them squeeze out a little extra efficiency in a time of extreme economic uncertainty.  

A race to focus on the basics

Unlike with previous waves of technology adoption, healthcare and life science organizations know exactly what they want to achieve with GenAI, even if it might not be quite as clear how to achieve it. 

Efficiency and optimization are the name of the game, according to a new poll by McKinsey & Company, which asked 150 stakeholders about their GenAI plans during the fourth quarter of 2024. 

A solid 85% of organizations were exploring or have already adopted GenAI in some capacity, the poll revealed, with the majority of the remaining respondents actively looking to pursue projects in the next 12 months. 

Three-quarters of respondents said that administrative efficiency and clinical productivity are their top GenAI goal, with payers leaning more heavily into streamlining operational processes and providers looking more toward improving workflows in the clinic. 

Patient engagement and quality of care were distant seconds, at 55% and 51% respectively, while research, education, strategy, and growth trailed far behind on the list of urgent priorities. 

Research from Nvidia found similar themes, with practical use cases such as workflow optimization and natural language processing (NLP) of clinical documentation landing at the top of the list of objectives for payers and providers. Just under 30% of payers and providers identified operational efficiencies as their primary goal for AI adoption, followed by improving client outcomes (26%) and improving clinical-patient interactions (24%). 

Most payers and providers (63%) in that survey believe GenAI will be most useful for tasks involving coding and documentation in the near future, despite other digital health and life science entities focusing on accelerating R&D, improving medical imaging and diagnostics, or enhancing the precision and accuracy of clinical insights. 

Build, buy, or borrow?

Leaders largely acknowledge the need to spend on GenAI sooner rather than later, although 68% of respondents to the Nvidia poll believe their organizations aren’t devoting enough budget to AI use cases at the moment. 

Those that have gotten the green light, however, are looking outside of the traditional build-or-buy paradigm. Instead, they’re exploring new types of partnerships with third-party vendors, including customized solutions from hyperscalers and cloud providers, technology consulting firms, and other IT solutions providers. 

Sixty-one percent of payers and providers are leveraging customized partnerships as a major component of their GenAI strategy, according to McKinsey, followed by just 20% who are planning to build tools in-house and 19% looking for buy off-the-shelf solutions. 

This indicates that organizations are not only increasingly aware of the challenges of taking on implementation and optimization work themselves, but may also understand that it might be worth investing a little more up front in a custom product than shouldering the unforeseen costs of in-house development or downstream optimization of standardized offerings. 

Achieving quick wins with measurable ROI  

Healthcare technology has always been aimed first at the low hanging fruit, and once again this tactic seems to be paying off. By using GenAI for prioritizing the optimization of processes instead of leaping straight to the sci-fi, organizations are, in fact, achieving ROI a little quicker than they might have anticipated. 

Overall, 64% of health systems, payers, and health technology groups in the McKinsey survey have achieved some form of ROI from their GenAI efforts, even if most of these organizations haven’t exactly calculated the return down to the dollar. 

Just over 80% of life sciences, biotech, provider, and payer organizations in the Nvidia report say the same, with 73% stating that AI has helped to directly reduce their operational costs. More than a third (36%) said their investments have created a competitive advantage, while similar numbers have reduce the time required for project cycles and enhanced the precision, accuracy, and delivery of insights. 

As a result, 78% of these organizations are planning to increase their spending in 2025 and beyond, with more than a third planning a budget hike of more than 10% in the coming year. Bucking the aforementioned trends somewhat, however, companies will be allocating their spending on additional use cases first, then prioritizing the optimization of their AI workflows and production cycles. 

Key takeaways from the GenAI adoption landscape

In general, healthcare and life science organizations are going all-in on GenAI. While clinical innovation and therapeutic R&D are still on the agenda for these industries, the majority of enterprises are first looking to leverage GenAI to stabilize their financial footing as workforce woes continue and an unpredictable regulatory environment makes it difficult to plan ahead. 

There’s certainly nothing wrong with this approach. Streamlining prior authorizations might not be as thrilling to talk about as robot doctors roaming the hallways, but it represents a degree of maturity and deliberation in the digital decision-making process that might have been missing in previous technology adoption cycles. 

GenAI is already showing itself as a powerful tool in helping organizations cope with administrative bloat and tame operational disorder, and will no doubt continue to do so as the industry generates more knowledge about how this technology can further its important goals. 

For organizations that are starting their GenAI journey, it will be important to think carefully about use cases that can return maximum value for minimal lift, and how to reinvest the gains to build momentum for future projects that further improve efficiency and ultimately enhance the sustainability of the organization as a while. 

Jennifer Bresnick is a journalist and freelance content creator with a decade of experience in the health IT industry.  Her work has focused on leveraging innovative technology tools to create value, improve health equity, and achieve the promises of the learning health system.  She can be reached at [email protected].