Real-Time AI for Healthcare Agents: Improving Patient Interactions

When cold and flu season intensifies, calls to healthcare contact centers surge. Patients and policyholders need help with appointments, insurance, prescriptions, billing, and more. That places added pressure on agents, whom patients rely on for accurate and empathetic service. 

Strong customer service is important in every industry, of course, but in healthcare, there’s extra urgency because every interaction may involve situations with serious medical and/or financial consequences. Agents need to be calm, tactful and prepared at every minute. Government regulations may also apply, depending on the situation, so being prepared may also require specific, additional training.  

Given all that’s at stake, agents need responsive and reliable support. Being ready and able to resolve every customer issue is non-negotiable. So is being ready and able to reassure customers that they’re in capable hands. Automation and emerging AI technologies offer opportunities to support agents more proactively, helping them work more efficiently while also preventing stress from eroding service quality. 

Reducing Agent Stress 

Agents overwhelmed by repeated high-stakes interactions may struggle to maintain focus, which increases the risk of errors and undermines customer confidence. The solution isn’t simply to add more staff—it’s to provide existing agents with the functional and emotional support they need to maintain consistent professionalism in the face of steady demand. 

On a functional level, automation and new AI-driven tools can improve service by analyzing real-time patient inquiries, assessing agent expertise, and directing calls to the most appropriate agents. This will reduce frustration for both patients and agents while improving first-call resolution rates. Real-time automation can also help maintain supply and demand balance during peak demand periods by dynamically adjusting scheduled breaks and redistributing calls. 

Technology-powered virtual assistants can also provide agents with real-time access to relevant policy information, coverage guidelines, and medical terminology. Instead of manually searching through multiple systems, agents can receive on-screen prompts and recommendations, enabling them to respond faster and more accurately. This type of instant knowledge retrieval not only improves service efficiency but also reduces cognitive load on agents, allowing them to focus on engaging with patients rather than scrambling for information.

On an emotional level, AI tools can support call center agents’ wellbeing by reducing stress, automating tasks, and offering personalized coaching. By recognizing signs of fatigue or stress, AI tools can prompt breaks or wellness resources when needed. AI encourages self-care and connects agents to peer support, creating a healthier work environment. 

As new AI capabilities emerge, it’s important to use them as agent support tools—not as substitutes for human judgment or personalized communication. Patients seek reassurance and clarity from a fellow human being, not from robotic-sounding, AI-generated responses.

Enhancing Customer Trust 

Healthcare inquiries are often emotionally charged. A denied insurance claim, a delayed prescription, or a sudden change in medical treatment can trigger frustration or confusion. In high-stakes situations, how an agent responds matters just as much as the information they provide.

AI-powered real-time sentiment analysis can help agents navigate these conversations more effectively. Traditionally, this technology has been used post-call, allowing managers to review recordings and provide feedback for coaching purposes. AI is now gaining the ability to detect emotional cues in real time, which will help agents adjust their approach in the moment.

For example, if AI identifies rising frustration or distress in a patient’s tone, it can prompt the agent to slow down, use more empathetic language, or escalate the call to a supervisor. This type of real-time emotional intelligence can help ensure that patient interactions remain constructive and supportive, even in difficult situations.

Effective AI solutions require proper training on healthcare-specific datasets. Poorly trained AI can misinterpret customer intent, provide incorrect recommendations, or create additional confusion. To ensure success, AI must be integrated thoughtfully, with continuous refinement and human oversight.

Most importantly, AI should never be used to script agent responses. Patients seeking healthcare assistance value genuine human interactions, and most of us can quickly detect when we’re speaking with someone who’s not really engaged. AI should be focused on reducing agent workload and enhancing decision-making—allowing them to deliver compassionate, patient-centered support.

Promoting Human-Centered Healthcare

Emerging technologies present significant new opportunities to improve the efficiency and effectiveness of healthcare contact centers. By optimizing call routing, simplifying information access, and enhancing real-time emotional intelligence, AI can help agents manage heavy call volumes without compromising service quality.

That said, healthcare organizations need to implement AI with caution. Patients are still a long way from trusting bots to handle their personal health concerns. The most valuable application of AI is to support agents and ensure that they have the resources, the training, and the emotional well-being needed to help customers resolve their high stakes issues. 

Leveraging technology within a broader people-first approach will allow healthcare contact centers to reassure their customers with agents who are always ready to deliver exceptional service.

About Jennifer Lee

Jennifer has 20 years’ experience in the contact center industry with more than 15 years as a people leader. Throughout her career, Jennifer has served in a variety of roles in the contact center space, including operations, quality, workforce management, and client services. As Intradiem’s President and Co-CEO, Jennifer leads the operations and people management of the organization. Prior to this role, Jennifer has served as Chief Operating Officer, Chief Strategy Officer and has led the Customer Success organization.