America is entering a demographic transformation that will fundamentally reshape healthcare delivery. By 2034, older adults will outnumber children for the first time in our nation’s history. At the same time, millions of Americans already struggle to access timely, high-quality care. This convergence—rising demand alongside constrained capacity—requires a more deliberate and forward-looking approach to how we plan, deliver, and scale care.
Artificial intelligence (AI) offers an important opportunity to meet this moment. Not as a replacement for clinical care, but as a tool to better anticipate need, target interventions, and design systems that work for patients.
At West Health, our focus is clear: lower healthcare costs and enable seniors to successfully age in place with dignity and independence. Increasingly, we see AI as a valuable tool with significant promise, if leaders use it thoughtfully, particularly in three areas where the healthcare system must evolve quickly: predicting demand, stratifying risk proactively, and scaling care models that meet patients where they are.
No. 1 - Predicting Demand: From Reactive Systems to Proactive Planning
Traditional healthcare planning relies on historical trends and demographic projections—blunt instruments for anticipating the nuanced needs of aging populations. AI-powered predictive analytics can provide far more granular forecasting by analyzing patterns in social determinants, chronic disease progression, geographic distribution, and healthcare utilization to predict where and when demand will surge.
HealthTech Magazine's 2025 overview of AI trends highlights how predictive modeling is becoming essential for healthcare systems preparing for demographic shifts. These models can forecast not just overall patient volumes but specific types of demand: geriatric emergency department visits, home health service needs, specialty care requirements, and long-term care transitions.
Consider the practical applications. An AI system analyzing Medicare claims data, census demographics, housing patterns, and local economic indicators might predict that a specific suburban community will see a 40% increase in heart failure admissions over the next five years as its Baby Boomer population ages and existing residents experience disease progression. This allows health systems to proactively expand cardiology services, establish remote monitoring programs, and partner with community organizations on heart-healthy aging initiatives, rather than reactively scrambling when emergency departments overflow.
McKinsey & Company's analysis of digital transformation in healthcare emphasizes that investment priorities must align with demographic realities, and AI forecasting enables precisely this alignment by identifying where aging populations will stress existing capacity and what interventions could prevent crises.
The implication is clear: health systems that invest in predictive capabilities today will be far better positioned to manage demand tomorrow, shifting from reacting to volume to planning for it with precision.
No. 2 - Stratifying Risk Proactively: Seeing the Full Picture of Patient Need
For older adults, the drivers of health extend well beyond clinical care. Housing stability, access to food, transportation, and social connection all play a critical role in determining whether someone remains healthy at home or experiences avoidable decline.
Too often, these factors are not recognized until they lead to a crisis.
AI offers a promising way to better identify risk earlier by building bridges across traditionally siloed healthcare and community systems. This allows leaders and care teams to see the full picture. By connecting indicators such as missed medications, gaps in care, or financial strain, so they can better understand what is really happening across populations and intervene before those indicators translate into hospitalizations or long-term care placement.
At West Health, we have created tools that bring this broader view into focus. Through our West Health Mosaic platform, the National Aging Readiness Dashboard provides a comprehensive picture of how well communities are equipped to support an aging population. It brings together publicly available data from American Community Survey (ACS), Centers for Medicare and Medicaid Services (CMS), Behavioral Risk Factor Surveillance System (BRFSS), Centers for Disease Contral and Prevention (CDC), the U.S. Census, and more, into a single, accessible platform, allowing community leaders to see key indicators such as healthcare access, housing, transportation, and social supports in one place, by state.
As part of a broader intelligent care approach using AI, this type of platform becomes even more powerful. It moves beyond simply describing current conditions to enabling forecasting; helping leaders, city planners, policymakers, hospital systems, and community organizations anticipate where needs will grow and where targeted investments can have the greatest impact.
In doing so, it provides a clearer view of what is actually happening across communities, cutting through complexity and giving decision-makers the ability to plan more effectively, align resources, and act earlier.
This is how we begin to shift from episodic care to continuous, coordinated support, by meeting patients where they are, rather than waiting for them to enter the healthcare system in crisis.
No. 3 - Scaling What Works: Intelligent Care Starts with Intentional System Design
Intelligent care does not begin with technology. It begins with intention. It starts by asking a simple but essential question: how do we meet patients where they are, and how do we build systems that support them there?
Too often, healthcare is designed around institutions rather than individuals. For older adults in particular, that misalignment leads to fragmented care, unnecessary utilization, and higher costs. Reorienting care around the patient requires deliberate system design—aligning workflows and care delivery models to support the realities of daily life, not just clinical encounters.
Digital tools like AI can support this work, but they are not the center of it. They are enablers. The real driver is leadership—making intentional decisions to redesign care in a way that is coordinated, proactive, and centered on the patient.
This is the approach we are advancing through the West Health Accelerator at Mass General Brigham. Together, we are embedding this philosophy directly into care delivery. Integrating thoughtful automation and decision support into Epic so that clinicians are supported in real time to deliver more coordinated, patient-centered care.
Rather than adding new layers of complexity, this work focuses on hardwiring better care into existing workflows, ensuring that the right actions happen at the right time, with less burden on clinicians and better outcomes for patients.
This is what it means to scale what works: not simply introducing new tools, but building systems intentionally designed around patients—so they can remain in their homes, maintain their independence, and, when they do need hospital care, receive the right care to safely return home and continue living independently.
The Path Forward: Intelligent Care, Grounded in Patients
The aging of America is not a distant challenge—it is already underway. The question is whether our healthcare system will adapt in time.
AI offers a set of tools that can help us plan more effectively, intervene earlier, and scale care models that improve both outcomes and affordability. But its success will depend on how we use it.
Technology must remain grounded in the needs of patients. It must support clinicians, not replace them. And it must be implemented with a clear focus on outcomes: lowering costs, enabling better access to care, and improving quality of life.
At its best, AI enables a more thoughtful approach to care—one that is proactive rather than reactive, coordinated rather than fragmented, and centered on the individual rather than the system.
And importantly, what works for older adults, clear communication, accessible services, and care designed around the realities of daily life, ultimately improves care for everyone.
If we apply AI with that principle in mind, we have an opportunity not only to prepare for an aging future but to build a healthcare system that delivers better care for all.
Zia Agha, MD, is Chief Medical Officer of the West Health Institute and the Gary and Mary West Foundation, where he leads clinical strategy and partnerships to advance high-quality, lower-cost models of care that enable seniors to age in place with dignity and independence. A practicing physician and health services researcher, Dr. Agha previously served as Director of Health Services Research and Development at the VA San Diego Healthcare System and is a Professor of Medicine at the University of California, San Diego. He is a Diplomate of the American Board of Internal Medicine and holds an MD from Aga Khan University and an MS in Clinical Epidemiology from the Medical College of Wisconsin.