Health care transformation is the large-scale, long-term reimagining of how health care organizations deliver care, manage operations, and serve patients through technology, process change, and stakeholder alignment. As of 2025, the health care industry is in the midst of a far-reaching shift driven by changing consumer expectations, emerging technologies like artificial intelligence, and growing demand for more personalized experiences.
The single most important lesson for health care leadership is that transformation succeeds or fails in what Adam Kautzner, President of Evernorth Care Management and Express Scripts and EVP of Customer Personalization for The Cigna Group, calls the critical middle—the challenging phase between the launch announcement and the realized outcome, where most initiatives lose momentum.
In a recent episode of the Future Ready Leadership podcast, Kautzner shared insights on leading large-scale change management, improving affordability, and preparing for the future of AI in health care.
Transformation is a long-term commitment
Health care organizations are under constant pressure to innovate while continuing to deliver for the people they serve. But meaningful health care transformation rarely happens overnight.
As of 2025, the evidence is clear that transformation is an execution problem, not a vision problem. Approximately 70% of digital transformation efforts fail to achieve their intended goals, largely due to persistent challenges including legacy infrastructure, cultural resistance, and workforce limitations, according to McKinsey research cited in a 2025 review published in Sustainability. In health care specifically, only about 16% of providers reach the “win zone” of successful digital transformation, less than half the cross-industry average, according to BCG’s Global Digital Transformation Survey.
During the conversation, Kautzner discussed the complexity involved in modernizing health care experiences at scale. From technology and processes to stakeholder alignment and operational execution, transformation often requires organizations to rethink long-standing approaches while maintaining trust and continuity.
For health care leadership, this reinforces an important lesson: successful transformation is not defined by a launch date. It is defined by sustained execution across the years that follow.
Why the “critical middle” is where transformation succeeds or fails
Perhaps the most notable concept from the conversation was what Kautzner described as the critical middle. While organizations often invest significant energy in planning and announcing transformation efforts, the most challenging work happens after the initial excitement fades.
The middle phase is where teams navigate the realities of implementation. The specific factors that most often derail transformation in this phase include:
Implementation fatigue — the energy that fuels a launch dissipates as day-to-day operational demands reassert themselves; more than one-third (35%) of health care tech leaders warn that transformation fatigue is likely to slow their agenda.
Stakeholder misalignment — employees, clients, and partners develop divergent priorities and expectations as the initial vision meets operational reality.
Communication gaps — the original vision is not consistently reinforced, leaving teams uncertain about direction and progress.
Competing priorities — new initiatives, regulatory demands, and market pressures crowd out the focus required to see transformation through to completion.
It is also where leaders must continue communicating the vision while ensuring employees, clients, and partners remain aligned around shared goals. For health plan leaders, employers, and benefits leaders, this stage frequently determines whether transformation initiatives ultimately achieve meaningful adoption and long-term impact.
The value of constructive skepticism
Another takeaway from the discussion was the role constructive skepticism can play in strengthening transformation efforts.
Rather than viewing questions and concerns as obstacles, Kautzner highlighted how feedback from employees, clients, and industry stakeholders can help identify blind spots, surface risks, and improve implementation plans. Leaders who create space for honest dialogue may be better positioned to balance innovation with practical execution, helping organizations move forward while maintaining trust.
These principles of sustained focus and open dialogue apply across every industry. But in health care, the stakes are uniquely personal: complexity does not just slow progress, it affects the people being served. That makes the work of simplifying experiences and deploying technology responsibly especially urgent for the organizations, employers, and benefits leaders who shape how people access care.
Simplifying health care experiences matters
Another theme throughout the discussion was the importance of reducing complexity for patients.
Health care consumers often encounter fragmented experiences, confusing benefit designs, and uncertainty about costs. Kautzner shared examples of efforts to create greater predictability and transparency within the pharmacy benefit experience, helping people better understand costs and access the medications they need.
For health plans employers, and benefits leaders, simplifying the health care journey remains a significant opportunity. Whether through benefit design, digital health experiences, or care navigation, organizations that reduce friction can help improve both member experience and engagement.
AI’s future in health care will depend on trust
The conversation also explored the growing role of artificial intelligence in health care. As of 2025, AI adoption in health care is accelerating rapidly: 22% of health care organizations have implemented domain-specific AI tools, a 7x increase over 2024 and a 10x increase over 2023, according to Menlo Ventures, with health systems leading at 27% adoption. Half of U.S. health care organizations have now implemented generative AI solutions, according to a McKinsey survey from Q4 2025.
Kautzner expressed optimism about AI’s potential to support greater personalization, consistency, and efficiency across health care experiences while emphasizing the need for careful implementation. In health care, accuracy and trust are essential, making human expertise and oversight critical components of any AI-enabled strategy. The key trust requirements for responsible AI adoption in health care include:
Accuracy — AI outputs must be clinically reliable and validated before they inform decisions affecting patient care.
Transparency — organizations must be able to explain how AI-enabled decisions are reached and where AI is being used.
Human oversight — qualified professionals must remain in the loop to validate, interpret, and override AI-generated recommendations.
Responsible governance — organizations need clear policies, accountability structures, and guardrails ensuring technology enhances rather than replaces informed decision-making.
As AI capabilities continue to evolve, health care organizations will need to balance innovation with these governance principles, ensuring that technology enhances, rather than replaces, informed decision-making.
Looking ahead
The health care industry is entering a new era of transformation driven by changing consumer expectations, emerging technologies, and growing demand for more personalized experiences.
As Kautzner shared during the discussion, the greatest challenge often is not defining a vision for change, but leading organizations through the years of work required to bring that vision to life. For health care leaders, success may depend less on how transformation begins and more on how effectively they navigate the critical middle.
