The Power of Many: How Agentic AI Works to Solve Healthcare Challenges
In healthcare, solving challenges always requires more than a single step. From scheduling appointments and verifying insurance to managing care transitions and reducing no-shows, the path to better patient outcomes is rarely straightforward. Just as healthcare organizations rely on interconnected systems like electronic health records (EHRs) and practice management software, AI solutions are most effective when they work together seamlessly.
This is where agentic AI comes in. Agentic AI refers to a system of specialized AI agents—each designed to perform specific tasks—working in coordination to achieve a larger goal. Think of it as a team of experts, each contributing their skills to move a patient smoothly through their care journey. By handling tasks autonomously, these agents reduce administrative burdens and allow healthcare teams to focus on what they do best: caring for patients.
At Luma Health, we believe the future of healthcare lies in the collaboration of AI agents. Our AI-powered Navigator solution uses agentic AI to streamline workflows, improve patient experiences, and drive measurable outcomes. From automating routine tasks to providing actionable insights, our network of AI agents supports both operational and patient care teams in delivering exceptional care.
In this blog post, we’ll explore how multiple AI agents work together to solve complex healthcare challenges, the benefits of agentic AI, and how Luma Health is helping providers navigate this new era of intelligent automation.
What is Agentic AI and How Does it Work?
Agentic AI is like having a team of digital assistants, each with its own role, working together to achieve a common goal. Each agent is specialized, meaning it has a clear task—whether that’s gathering data, analyzing information, or triggering actions.
As Ivan Viragine, AI Engineering Manager at Luma Health, explains: “An agent is a combination of a large language model (LLM), a prompt, and a set of tools. In Navigator’s case, we have one agent for verifying a patient’s identity, another for listing appointments, and others for tasks like confirming visits. These agents work together to achieve their goal of understanding and fulfilling the user’s request.”
These agents coordinate in real time, adjusting their actions based on new information. For example, if a patient cancels an appointment, one agent verifies the patient’s identity, another lists the upcoming appointments to confirm which one to cancel, and a third cancels it directly in the EHR. This intelligent division of labor reduces administrative burden and ensures patients receive timely care.
This multi-agent or “agentic AI” approach also improves accuracy and reliability. Instead of relying on a single AI to parse an overwhelming set of rules or data—like expecting one person to memorize and apply a 100-page manual—agentic AI distributes the cognitive load. Each agent focuses on a smaller, well-defined domain (like one chapter of that manual), and a coordinating supervisor directs requests to the most relevant agent. This specialization not only speeds up performance but also reduces the risk of error or confusion—especially critical in healthcare, where mistakes can have serious consequences. The result is a system that’s more capable, precise, and less prone to “I can’t help you with that” dead-ends.
Why Healthcare Needs Agentic AI Systems
Healthcare operations are inherently complex. From scheduling and follow-ups to prior authorizations and patient communications, these processes often require complex coordination with large groups of people. Disconnected systems lead to inefficiencies, delays, and frustrated patients. On top of that, healthcare staff are burdened with administrative tasks—research shows that clinicians spend nearly 50% of their time on paperwork and administrative work, taking away from patient care.
Healthcare needs multi-agent AI systems. Many real-world patient interactions are too nuanced for a single agent to manage. Imagine a patient who wants to cancel her upcoming PCP appointment and refill her child’s prescription—all within one call to the clinic’s access center. A common scenario, yet far too intricate for traditional, monolithic AI systems to handle effectively. This is where multi-agent AI shines.
One way to understand the power of agentic AI is through analogy: imagine asking a person to memorize a 100-page instruction manual and then locate the answer to a very specific question. The likelihood of them missing or mismanaging the task is high—because the answer might live in a tiny paragraph on page 56. But if you break the manual into chapters and assign a smaller expert to each one, then have a supervisor route questions to the right expert, accuracy improves dramatically. Each specialized agent only needs to sift through a narrow slice of information, which significantly reduces the risk of misunderstanding or error.
This is especially critical in healthcare, where the consequences of a mismanaged task can directly affect patient safety or delay care. Smaller, specialized agents reduce cognitive load and hallucinations—two well-documented risks in large language models—resulting in more reliable performance.
Think of agentic AI like a surgical team. Each member—surgeon, anesthesiologist, nurse—has a well-defined role. Similarly, AI agents specialize in distinct functions:
- Data collection agent: Gathers patient information from EHRs and appointment systems.
- Analysis agent: Reviews that data to detect care gaps or conflicts.
- Action agent: Sends reminders, confirms appointments, or alerts care teams.
As Hwee Min Loh, Senior Product Manager at Luma Health, describes it: “Agentic AI means that the reasoning framework is spread across multiple specialized agents, rather than relying on one massive list of instructions. This reduces common issues like hallucination and enables more accurate, reliable outcomes. Navigator ensures all patient requests are directed to the right specialized agents.”
Real-World Use Cases of Agentic AI in Healthcare
At Luma Health, we see the impact of agentic AI systems every day. One compelling example is our work with UAMS (University of Arkansas for Medical Sciences). Faced with rising call volumes and patient communication challenges, UAMS partnered with Luma Health to deploy our Navigator AI platform.
With Navigator’s agentic AI approach:
- Intelligent routing: Calls and messages were automatically routed to the right AI agent based on patient intent, and transferred to a staff member if Navigator could not support that request today.
- Automated schedule checking: Agents assisted in verifying patient identity, looking up appointment information, and assisting with appointment confirmation or cancellation
- 24/7 support: Patients are able to get information about their upcoming appointments and take appropriate actions anytime.
The results were transformative—UAMS saw a 20% decrease in patient no-shows and significantly reduced call center volume. Staff were freed from repetitive tasks, allowing them to focus on providing high-value care. Learn more in our UAMS case study.
Looking Ahead — The Future of Agentic AI in Healthcare
The future of multi-agent AI in healthcare is exciting. As AI systems become more adaptive, predictive, and personalized, hospitals will increasingly rely on agentic AI to anticipate patient needs and proactively manage care.
- Adaptive systems: Agents will learn from real-time data to refine decision-making and respond to evolving situations, ensuring continuous process improvement.
- Predictive insights: AI agents will leverage advanced analytics to predict patient risks, recommend preventive interventions, and reduce hospital readmissions.
- Personalized experiences: Patients will receive tailored communication and support through AI-driven interactions that account for their medical history and preferences.
Healthcare organizations will further integrate agentic AI for proactive care management—reducing administrative burdens, improving operational efficiency, and ultimately enhancing patient outcomes. At Luma Health, we’re excited to continue leading this transformation, empowering providers to deliver exceptional care through the power of many AI agents.
AI Agents Must Collaborate
No single AI agent can solve healthcare challenges alone. Just as healthcare providers work as teams, AI agents are most effective when they collaborate to streamline operations and enhance patient care.
At Luma Health, we are committed to applying the power of multi-agent AI to make healthcare easier for providers and patients alike. By leveraging Navigator’s agentic workflow, we help healthcare organizations reduce administrative burdens, improve operational efficiency, and ensure patients receive timely, high-quality care.
Want to see how multi-agent AI can transform your organization? Learn more about Navigator or request a demo today to experience the Luma Health difference.
Frequently Asked Questions
How does agentic AI integrate with our existing systems like EHRs or practice management software?
Luma’s Navigator platform is designed to integrate seamlessly with leading EHRs, scheduling systems, and communication tools. Whether you’re using Epic, Cerner, Athenahealth, or other platforms, our AI agents can access and act on real-time data through secure API connections and industry-standard integrations.
What is the implementation timeline? How much lift is required from our IT team?
Most organizations see their first AI workflows live within weeks. Our dedicated team handles the heavy lifting of that first implementation, with minimal demands on your IT resources. We tailor the rollout to your existing workflows and provide hands-on support to ensure a smooth transition. There are also self-serve tools available so that you can build your own workflows in a no-code, easy-to-use interface using Navigator’s individual agentic AI skills.
Is this secure and HIPAA-compliant?
Yes. Security and compliance are non-negotiable. Luma Health is HIPAA-compliant and HITRUST-certified, and all agent actions are fully auditable. Our platform ensures patient data is handled securely at every step, with encryption and strict access controls built in.
Will Navigator replace my staff?
Navigator is designed to augment, not replace, your team. By taking on repetitive and time-consuming tasks like scheduling, appointment reminders, and eligibility checks, our AI agents free up your staff to focus on high-value interactions that improve the patient experience and operational outcomes.
What happens when the AI doesn’t know what to do?
Agentic AI is built to collaborate—with each other and with your team. When an agent encounters a complex or ambiguous request, it automatically escalates the task to a human staff member. Patients never hit a dead end, and your team is always in the loop.
How do I measure the ROI of agentic AI?
Navigator includes built-in analytics that track key performance metrics—reduction in call volume, no-show rates, scheduling efficiency, and more. Our clients often see measurable impact within the first few weeks of deployment.
Can we customize workflows or agent behavior?
Yes. Each Navigator agent can be configured to fit your needs, such as modifying the welcome and end message, the agent’s voice, and the action it can take with your patient. Whether you want agents to follow specific scripts, recognize custom intents, or trigger internal protocols, we give you the flexibility to stay in control. There are also self-serve tools available so that you can build your own workflows in a no-code, easy-to-use interface using Navigator’s individual agentic AI skills.
How do patients feel about interacting with AI agents?
Patients appreciate fast, 24/7 access to the help they need—without waiting on hold. Our Spark AI is designed to be transparent and patient-friendly, clearly indicating when they’re interacting with a digital assistant. When needed, agents seamlessly hand off to staff, ensuring a smooth and trusted experience.