For years, the promise of artificial intelligence (AI) in healthcare has been a tantalizing vision on the horizon, a concept discussed in boardrooms and at industry conferences. That future is no longer a distant concept – it is our current reality. The dialogue among healthcare leaders has decisively shifted from if to how. The focus now is on strategically implementing AI to drive tangible value for their organizations, improve patient outcomes, and enhance the work-life of clinicians.
Substantial Investment Meets Strategic Patience
Despite economic uncertainty, AI has become a primary investment focus, with a majority of healthcare leaders viewing it as a top priority. This strategic imperative requires robust board-level governance to align both the opportunities and the inherent risks. Leaders are ensuring there is a clear, top-down strategy for offensive and defensive plays, acknowledging that while many are preparing to allocate significant portions of their budgets to AI, the return on that investment will take time to materialize.
Beyond Technology: The Human Element
The initial wave of AI adoption has already demonstrated its value, with many healthcare organizations having reported efficiency gains from their AI initiatives. Yet, significant barriers prevent many from scaling the summit. For numerous leaders, the primary challenge is integrating AI into existing organizational processes. This highlights a crucial truth: successful AI adoption hinges as much on change management and workforce readiness as it does on the technology itself.
A Roadmap for Transformation: Enable, Embed, Evolve
To navigate this complex journey, a deliberate, three-phased approach to value creation is required: enabling the foundations, embedding intelligence across the enterprise, and evolving toward a new kind of healthcare ecosystem.
Phase 1: Building the Foundation
The initial “Enable” phase is the most critical. It’s about building a solid foundation by establishing a clear strategy and a modern, interoperable data infrastructure. Many healthcare leaders identify poor data quality as a major constraint. Breaking down these silos is non-negotiable. Success here is also about people. With a strong focus on retraining talent for an AI-enabled future, it’s clear that building trust and demonstrating AI’s role as a supportive co-pilot – not a replacement – is paramount.
Phase 2: Embedding Intelligence into Workflows
Once the foundation is set, the “Embed” phase can begin. This is where AI moves from the lab to the frontline of care delivery. By integrating AI into core clinical and operational workflows – from automating the many administrative tasks that leaders see as ripe for improvement to enhancing diagnostic support – organizations can realize significant efficiencies. This not only improves care quality but also directly addresses the critical issue of professional burnout by allowing clinicians to focus on what they do best: care for patients.
Phase 3: Evolving into Intelligent Ecosystems
Finally, the “Evolve” phase represents the pinnacle of AI-driven transformation. Here, healthcare organizations create intelligent, interconnected ecosystems that extend beyond the hospital walls. In this phase, care becomes proactive and deeply personalized. It is about building a system that delivers holistic, patient-centered care, seamlessly integrated into daily life.
The Journey to a Smarter Future
The journey to becoming an intelligent healthcare organization is a marathon, not a sprint. It requires a clear vision, sustained investment, and a culture that embraces change. The leaders who succeed will be those who move beyond the hype, focus on strategic implementation, and build a future where AI enhances human touch, creating a more resilient and patient-centered health system for all.
Drew Corrigan
Drew Corrigan is the U.S. Healthcare Sector Leader at KPMG. Drew previously served as the Managing Partner for the KPMG Portland office and has more than 25 years of experience, primarily serving large not-for-profit health systems, academic medical centers, and payors.
