Today we’re joined by Faisal Zain, a leading expert in medical technology who has spent his career at the intersection of healthcare innovation and strategic leadership. We’ll be exploring a seismic shift occurring in the C-suites of health systems across the country: the elevation of technology from a support function to the very core of enterprise strategy. Our conversation will delve into the emergence of new executive roles designed to harness the power of AI and data, the unique challenges of implementing these strategies in diverse settings from rural communities to vast urban networks, and the critical importance of establishing robust governance to ensure technology serves patients and caregivers effectively and ethically.
Rural health systems often face unique challenges like workforce shortages and thin margins. How can a dedicated Chief Transformation Officer leverage AI and data to address these specific issues and advance value-based care? Please share a practical example of how this works.
That’s the fundamental question many systems, especially those in resource-constrained areas, are wrestling with. For a rural system like Sanford Health, which serves communities spread across the Upper Midwest, these aren’t theoretical problems—they are daily realities. A Chief Transformation Officer’s role is not just to implement new tech, but to wield it as a strategic weapon against these very challenges. Imagine using predictive analytics to forecast patient surges in specific clinics, allowing for smarter staff scheduling to combat workforce shortages. Or think about leveraging AI-powered diagnostic tools to support primary care physicians in remote areas, reducing the need for patients to travel long distances for specialist consultations. This isn’t about technology for technology’s sake; it’s a direct line to improving access and strengthening performance in value-based care models, where keeping people healthy in their communities is the ultimate goal.
As technology shifts from a support function to a core value driver, how does creating a new tech-focused executive role change the dynamic with the traditional CIO? What steps can organizations take to define these roles clearly and prevent conflict or overlap?
This is a critical point of friction if not managed correctly. Historically, the CIO was the guardian of infrastructure—the pipes, the servers, the EHR’s stability. It was an essential but fundamentally operational role. The new generation of tech leaders, whether a Chief Transformation or Digital Officer, is focused on enterprise value creation. They’re asking, “How can we redesign the entire care model using these new digital capabilities?” To prevent conflict, the C-suite must be deliberate and clear. The CEO needs to champion the vision that the CIO ensures the foundation is rock-solid, while the new tech leader builds the innovative structures on top of it. Formalizing governance committees and creating clear escalation pathways are also vital. This ensures that when decisions are made, everyone understands their lane and is pulling in the same strategic direction, rather than getting caught in a turf war over who owns which project.
These new tech leaders often report directly to the CEO, creating a single point ofaccountability for transformation. What are the key metrics they should be measured against to prove ROI, and how do they translate these complex technology outcomes for the board?
The metrics absolutely have to shift from traditional IT measures. The board isn’t interested in server uptime; they want to see a direct impact on the organization’s strategic goals. This means the new leader must be measured on things like improved patient access, reductions in clinician administrative burden, or measurable gains in value-based care performance. Their job is to be a storyteller and a translator. They need to connect the dots for the board, explaining, “Our investment in this AI-driven workflow tool didn’t just ‘get deployed’; it reduced nurse charting time by 15%, which directly addresses our staff burnout problem and improves patient safety.” It’s about translating complex technology investments into the language of clinical, financial, and operational outcomes that the board understands and values.
Some systems frame digital transformation as a change management effort focused on redesigning workflows, not just deploying tools. Could you walk us through the process of aligning a major tech initiative with frontline clinical realities to ensure it actually improves caregiver experience and operational performance?
This is the most important part of getting it right, and a place where many initiatives fail. The approach taken by organizations like MUSC Health is exemplary. It begins not with the technology, but with the people. You don’t walk into a clinical unit and announce, “Here is your new AI tool.” Instead, you start by shadowing nurses and doctors, sitting with them, and understanding the friction in their day. Where are the bottlenecks? What administrative tasks are burning them out? You co-design the solution with them, framing the initiative as a way to solve their problems. This way, the technology becomes a natural enabler of a better, more efficient workflow that they helped create. It stops being a top-down mandate and becomes a collaborative effort to improve how care is delivered, which is the only way to ensure genuine adoption and a positive impact on performance.
With the rise of roles like a Chief AI Officer, establishing strong governance is critical. What are the essential components of an effective AI oversight committee, and what “guardrails” must be in place to ensure new AI tools are deployed safely, ethically, and equitably?
The moment you begin deploying AI into clinical workflows, you take on an immense responsibility. The “guardrails” are non-negotiable. An effective AI oversight committee, like the one established at Cleveland Clinic, must be multidisciplinary. It needs clinicians who can validate the tool’s clinical appropriateness, data scientists who understand the algorithms, ethicists who can probe for potential biases, and operational leaders who grasp the workflow implications. Key guardrails include a rigorous vetting process for any new AI tool to ensure it is built on diverse and representative data to avoid perpetuating health inequities. There must be transparent policies for how AI-driven insights are used in decision-making and clear pathways for clinicians to override the technology when their judgment dictates. The goal is to create a framework that both encourages innovation and guarantees that patient safety and ethical principles are the absolute top priorities.
For a large public health system, coordinating care across a vast safety-net environment is crucial. How does elevating data and AI oversight to the executive level help improve system-wide decision-making in real-time? Can you provide an anecdote where this approach made a tangible difference?
In a massive, complex system like NYC Health + Hospitals, operational coordination isn’t a luxury; it’s a lifeline for the community. When you have dozens of facilities, you can’t afford to have siloed data or fragmented decision-making. By creating executive roles like a Chief Data and AI Officer, you are deliberately putting real-time intelligence at the leadership table. This allows the system to see the entire landscape at once. For instance, instead of one hospital being overwhelmed with ER visits while another has open beds, an executive with system-wide data oversight can see that imbalance in real-time. They can then direct resources, reroute ambulances, and manage patient loads dynamically across the entire enterprise. This shift from reactive, facility-by-facility problem-solving to proactive, system-wide management makes a tangible difference in efficiency and, most importantly, in patient care.
What is your forecast for the evolution of technology leadership in health care over the next five years?
Over the next five years, I believe the line between “technology leadership” and “executive leadership” will effectively disappear. We will no longer see technology as a separate department or strategy; it will be inextricably woven into every clinical, financial, and operational decision. The Chief Transformation or AI Officer of today will likely become the CEO or COO of tomorrow, as a deep understanding of data, digital workflows, and AI becomes a prerequisite for leading a modern health system. The debate will move beyond which C-suite title is best and focus instead on cultivating a leadership culture where digital fluency is as fundamental as financial literacy. The systems that thrive will be those that have fully embraced this reality, making technology the central nervous system of their entire organization.
