Why Incremental Change in Healthcare is No Longer an Option

Last month’s annual McKinsey's Healthcare Conference left me with a renewed sense of urgency and optimism about the healthcare industry's potential for meaningful transformation. The panel discussions and conversations among 250 leaders from health systems, payer organizations, and health tech innovators, unearthed critical insights. These findings must shape the industry’s choices and actions as it navigates the daunting challenges ahead.

A striking theme emerged: a widespread acknowledgment that healthcare systems can no longer afford incremental change. Eduardo Conrado, president of Ascension—one of the nation’s largest healthcare providers—emphasized that health systems must leverage their balance sheets strategically to fund genuine innovation. This isn't about small pilot programs or peripheral improvements—it's about fundamentally reimagining how we deliver care.

Also, during the conference, a few factors were identified as significant challenges to the current system. Several speakers highlighted the lack of aligned incentives among providers, payers, and other stakeholders, including the pharmaceutical industry. The consensus was clear: until we align the interests of all stakeholders around patient outcomes rather than volume; we'll continue to see suboptimal results.

Value-based care, a model I strongly support, continues to hold immense promise for aligning financial and clinical incentives to keep patients healthy. Intermountain Health—a leader in rethinking care model design—as well as other health systems, highlighted a clear shift to more proactive care management model that focuses on keeping patients well and out of the hospital.

But to achieve real scale, these models need robust support from AI, which can streamline key processes such as risk stratification, manage complex quality metrics, close care gaps, and track the diverse requirements in multiple, simultaneous risk contract arrangements.

Conference attendees called for a fundamental “reset” in how payers and providers work together. They urged greater collaboration to mitigate the adversarial elements of the relationship that have increased in recent years. Prioritizing the automation of data exchange between health systems and their payers will be critical, not only for operational efficiency but to also improve patient access to care.

The workforce crisis emerged as perhaps the most pressing problem facing the healthcare industry through 2030. Shortages, retention issues, burnout, and geographic maldistribution of healthcare workers present a dual reality: our greatest challenge and our greatest opportunity. The organizations that leverage technology to support and optimize their talent—both clinical and administrative—will have a significant competitive advantage.

The financial strain that many health systems are experiencing, because of these pressure points, is paradoxically creating opportunities for transformation. When organizations are compelled to make bold decisions about their future, they often discover innovative solutions they might never have considered during more comfortable times.

This economic pressure drives healthcare systems to explore new care models, consolidate services, and invest in truly scalable innovations over one-off solutions.

Paul Markovich's observation—"you can't put AI on top of a fax machine"—rings true. The healthcare industry has spent too long trying to bolt new solutions onto outdated platforms and protecting data in commercial silos. As a result, we’re essentially driving a Model T in a world of modern cars.

The promise of AI to improve care quality and access, enhance clinician engagement, and lower healthcare costs will only be fulfilled when we commit to the hard work of modernizing our underlying systems and processes. This means migrating data to the cloud for security and more efficient operations, eliminating the data silos that have plagued healthcare for decades.

Kim Keck of the Blue Cross Blue Shield Association beautifully reinforced this point: the data needed to build high-performing care networks already exists. The challenge, Beck argued, is effectively activating it. To do so, we need to stop thinking about AI as a siloed tool and instead view it as a horizontal capability that can transform every aspect of healthcare delivery.

As I reflect on the conference discussions, I'm struck by how the conversation has evolved. We're no longer debating whether transformation is necessary—we're focused on how to execute it effectively. The health systems that will thrive are those that embrace this moment of disruption, align incentives with patient outcomes, and commit to the infrastructure investments needed to support the transformational change that agentic AI is poised to create.

The path forward requires courage, collaboration, and a willingness to challenge long-held assumptions about how healthcare should work. The good news is that the tools, knowledge, and economic incentives are finally aligning to make meaningful transformation possible.