In the future, we imagine a workforce where AI and humans can work seamlessly to complete not only individual tasks, but end-to-end processes. Even further, voice AI agents will be able to operate autonomously and communicate with other voice AI agents to share information, coordinate actions, and make decisions. The agents work in lock step with their human healthcare counterparts, and together create an experience for patients that is far more streamlined than anything we’ve experienced before. 

This future is not far away. Today’s voice AI agents can automate interactions across the patient, payor, and provider experience, helping healthcare organizations of all kinds save human time for more creative tasks and fulfilling patient interactions. Voice AI agents can automate routine tasks – whether those tasks are simple (e.g., calling a provider to confirm their address) or more complex (e.g., answering a question about a medication’s side effects). 

To understand these agents and their capabilities, it can be beneficial to think of voice AI agents for healthcare as falling into one of three buckets:

Patient-facing AI agents

We know two things: Patiåents want calls from their healthcare providers, and phone calls made by humans don’t scale. AI agents can help solve for this gap, by taking on some routine but necessary calls made to patients.

Some examples of patient-facing calls voice AI agents can make today include:

Welcome calls: Calls made by patient support programs to individuals beginning treatment. On these calls, AI agents can answer questions and set expectations, helping to personalize the patient experience.

Medication adherence calls: Data shows that adherence rates increase when nurses call patients to check in. AI agents can handle such calls, proactively checking in to ensure patients are taking medication as prescribed, and can escalate reported side effects or any blockers to clinicians and/or case workers. 

Health or financial risk assessments: AI agents can help ensure patients get the most out of their insurance plans by performing routine health assessments.

Payor-facing AI agents 

It’s widely understood that administrative overwhelm leads to healthcare worker burnout. In fact, in a study we conducted of 250 healthcare workers, we found that the insurance/authorization process was the most frequently cited cause of burnout. Payor-facing AI agents can take on this phone-based work, enabling healthcare workers to reallocate their time to spend on higher-value, patient-facing work.

Some examples of calls to payors that AI agents make today include:

Benefits and insurance calls: AI agents can navigate payor and pharmacy benefit manager interactive voice response (IVR) systems, wait on hold, and collect detailed benefits data from human representatives.

Prior authorization calls: Like with benefits calls outlined above, AI agents can capture data including prior auth requirements and check for status updates.

Claims and Appeals: Today’s AI agents can perform claim status, appeals, and over-the-phone claim submissions, navigating IVR and hold and performing these tasks by conversing with a human representative on the other end of the line.

Provider-facing AI agents

As with patients, phone calls to providers are necessary but do not scale. AI agents can be helpful here, to both create new touchpoints and automate existing ones, helping ensure healthcare providers are able to get information they need (or share important information) at the right time.

Some examples of calls to healthcare providers that AI agents are making today include:

Directory confirmation calls: AI agents can call providers to verify their information (location, specialty, insurance network status, etc.) so they can be discovered by patients in online directories and more.

Provider education calls: AI agents can call providers supporting patients on specialty medications by answering their questions, setting expectations, and helping them improve the patient experience so they can operate at the top of their licenses.

Missing information calls: AI agents can call providers to collect missing information when documentation is submitted – for example, a provider’s address may be missing. By automating these touchpoints, delays in patient access, as well as challenges with adherence or affordability of therapy can be avoided.

Want to learn more about agentic AI in healthcare – both where we are today and where we’re headed? We’ve got a guide for that. Download The Agentic AI Workforce is Coming to Healthcare today.