The right patient at the right time with the right provider
Healthcare AI today is focused on alleviating administrative burdens, including solving documentation challenges for clinicians and managing revenue cycle complexity for operators. These are important use cases, helping to reduce the $4.5 trillion spent annually on American healthcare. However, they do not address the care delivery moment itself—nor the biggest challenge in healthcare: the supply and demand imbalance.
American healthcare is moving further from economic equilibrium every day. Patient demand is growing more complex, driven by an aging population and rising chronic disease rates. Meanwhile, the clinician shortage continues to deepen, leaving the healthcare system unprepared to meet this growing demand.
AI’s greatest impact on access, cost, and quality will come from integrating intelligent systems into workflows at the point of care. This integration has the potential to transform interactions between providers and patients, enabling healthcare systems to create delivery models rooted in abundance rather than scarcity.
The future of healthcare is unlikely to include significantly more providers. Instead, it will feature care models that leverage AI Agents to optimize core "jobs to be done." This approach will create equilibrium, ensuring the right patient is seen at the right time by the right provider.
How AI can impact patient demand
Access barriers often prevent patient demand from connecting with the appropriate supply. Patients face limited knowledge about where to start their care journey, fragmented pathways, and insufficient provider availability. These challenges are exacerbated by the complexity of a healthcare system fragmented by silos.
AI has the potential to eliminate these barriers through personalized navigation and scalable patient engagement. A foundational element of these tools is their reliance on a patient’s comprehensive medical history. For example, a headache in a 30-year-old woman could signal flu symptoms, side effects from oncology treatment, or a sports-related injury—each of which requires a different care pathway. An AI Agent anchored in a patient’s electronic medical record (EMR) integrate broader medical histories with current complaints to create a nuanced understanding of demand. This ensures patients are routed to the appropriate provider.
AI also enables proactive engagement with patients, going beyond reactive care. AI Agents can deliver personalized health information, conduct automated outreach to close care gaps, and monitor chronic conditions for escalation when necessary. These agents will increase continuity of care and drive quality improvements by encouraging behavior changes and timely interventions.
How AI can augment provider supply
On the supply side, the shortage of clinicians is severe and trending towards catastrophe. Building on challenges with retention and burnout, clinicians often lack the technology and information at the point of care that could amplify their capacity. This leads to mismatches in supply and demand—for instance, cardiologists managing hypertensive patients with well-controlled blood pressure—while limiting the tools available to provide efficient care.
AI can transform this dynamic by augmenting the “jobs to be done” for clinicians and integrating seamlessly into their workflows. As a historian, AI synthesizes patient data from diverse sources, including EMRs, to provide a personalized, context-rich investigation of each patient’s needs. These insights are delivered to clinicians at the point of care, enabling them to focus on complex problem-solving and patient education. This approach enhances productivity while also improving care quality, thanks to consistent, comprehensive data availability for diagnosis and treatment.
These benefits are already being realized by K Health, a clinical AI company partnering with leading health systems such as Cedars-Sinai and Hackensack Meridian Health. Using K Health’s platform, primary care providers receive AI-collected insights at the point of care, streamlining workflows and enhancing care delivery. This delivery model, which embeds Virtualists using K’s AI tools into existing primary care teams, has the potential to expand access and panel size while maintaining high quality standards.