Use Cases & Examples [’25]

AI agents in healthcare are transforming the way care delivery, diagnostics, operations, and patient engagement work. Unlike traditional software, these intelligent systems leverage machine learning and natural language processing to perform tasks that previously required human judgment, speed, and intuition.

Their role has expanded from automating isolated administrative tasks to supporting complex clinical decision-making and enhancing the patient experience at every touchpoint.

Explore the top 10 AI agents in healthcare, including their features, use cases, benefits, and future trends.

Comparing the top 10 AI agents in healthcare

Note: The table is sorted based on the number of reviews obtained from B2B review platforms like G2 and Capterra, except for our sponsor at the top. We did not include pricing information as all vendors require a demo and do not provide a free trial/plan.

AI agents in healthcare feature comparison

Detailed evaluation of healthcare AI agents

Sully.ai

Sully.ai provides an all-in-one virtual assistant tailored for healthcare environments, offering support across clinical, administrative, and front-desk operations. It assists nurses with patient care and monitoring, helps medical assistants with vitals and scheduling, and serves as a real-time scribe to document encounters and update EHRs.

Sully also accurately automates medical coding, manages appointments and patient communications as a receptionist, handles office tasks like scheduling and reporting as an admin assistant, and supports pharmacy operations by preparing and verifying prescriptions.

Figure 1: An example from Sully, the “Pharmacy Technician”, its features and checklist.

Cognigy

Cognigy is designed to handle appointment scheduling, triage symptoms, answer insurance and billing questions, and provide 24/7 support through voice and chat.

For example, Virgin Pulse, a global health engagement company, boosted its member support by deploying an AI Agent using Cognigy.AI. Integrated with Zendesk LiveChat, the bot was launched across key member platforms.

Within a month, the containment rate increased from 3% to 40%, achieving 97% intent recognition accuracy. It covers 29 topics, automated ticket creation, and is handed off to live agents when needed. User sessions more than doubled, and the project earned Virgin Pulse the Cognigy Newcomer Champion Award in 2024.

Amelia AI

Amelia AI is designed to deliver human-like, conversational support across patient and administrative services. It engages with patients to schedule appointments, answer medical inquiries, assist with insurance and billing questions, and provide follow-up care instructions

Also, Amelia AI agents integrate with systems like EPIC and Cerner to deliver personalized services at scale.

For example, ​Aveanna Healthcare, a pediatric and adult home health service provider, improved employee support by deploying Amelia’s AI agent to handle frequent internal requests like password resets and user authentication.

The AI agent manages over 560 daily conversations, resolving 97% of employee inquiries through Aveanna’s Workday portal and chat. This automation has reduced IT workload, allowing caregivers to focus more on patient care and enhancing overall operational efficiency.

Notable AI

Notable AI provides intelligent automation for healthcare operations through AI agents that manage tasks like patient intake, scheduling, referrals, and care gap closures.

It features a low-code Flow Builder for customizing workflows, real-time performance monitoring dashboards, and integration with systems like EHRs and CRMs to optimize processes and improve efficiency.

Hippocratic AI

Hippocratic AI provides a wide range of specialized AI agents, including care coordination and discharge support for surgical transitions and chronic and preventive care management for long-term health.

They also offer patient engagement, education tools to boost health literacy, and administrative assistance for tasks like advance directives and clinical trial enrollment.

The platform supports value-based care, specialty care areas like oncology and ophthalmology, and emergency preparedness, helping ensure consistent and personalized care throughout the patient journey.

Figure 2: Examples from Hippocratic AI agents ranging from disaster response to health risk assessment, diabetes, and post-surgery check-in.

What are AI agents in healthcare?

AI agents are autonomous or semi-autonomous systems that assist healthcare providers, payers, and patients across various functions. These agents can interpret patient data, engage in natural conversations, and execute actions such as scheduling appointments or flagging billing anomalies.

In contrast to rule-based bots or RPA tools, modern AI agents—especially those enabled by agentic AI—can adapt their responses and actions based on real-time data and conversational context.

They are deployed in clinical and non-clinical workflows, augmenting physicians, nurses, and administrative staff with real-time insights, guidance, and automation.

By interfacing with electronic health records (EHRs), diagnostic systems, and patient portals, they help healthcare systems enhance both operational efficiency and care quality.

Key features of healthcare AI agents

• Context-aware conversation: AI agents use natural language understanding to engage in patient interactions with personalized support. They can clarify intentions, handle complex dialogue turns, and explain data policies to build trust.
• Real-time decision support: These agents analyze real-time patient and population health data to guide diagnosis, recommend treatments, and prompt timely interventions.
• Multimodal data interpretation: AI agents process diverse inputs—from radiology images and EHRs to audio notes and lab reports—enabling holistic analysis.
• Task execution & automation: From automating scheduling to processing prior authorizations or billing tasks, AI agents reduce the administrative burden on human agents.
• Integration across systems: They interoperate with healthcare systems (e.g., EHRs, CRMs, and communication platforms) to offer care coordination and follow-up care.
• Self-learning capabilities: Agentic AI enables continuous learning, allowing agents to refine their actions and large language models based on ongoing interactions and outcomes.

Common use cases

Healthcare AI agents address clinical, operational, and patient engagement challenges across diverse applications:

1. Diagnostic support & medical imaging

AI agents can identify anomalies in X-rays, MRIs, and CT scans with accuracy that rivals or exceeds human radiologists. These systems analyze patterns in patient data to support early diagnosis for conditions like cancer, cardiovascular disease, or Alzheimer’s.

2. Personalized treatment & predictive analytics

AI agents personalize care pathways by combining genetic, lifestyle, and behavioral data. They can forecast treatment responses and adverse reactions, guiding clinicians in tailoring therapies to each patient’s needs.

In oncology, AI agents help determine optimal chemotherapy protocols that balance efficacy with minimal side effects.

3. Virtual health assistants & patient monitoring

AI virtual assistants provide 24/7 patient support—answering questions, reminding patients about medications, and alerting providers in case of abnormal vital signs. This supports proactive health management, especially for chronic care.

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