Top 10 AI Agents in Healthcare: 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 point of contact.

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 2024.¹

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.²

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 offers a comprehensive range of specialized AI agents, including care coordination and discharge support for surgical transitions, as well as chronic and preventive care management for long-term health.

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

The platform supports value-based care, specialty care areas such as oncology and ophthalmology, and emergency preparedness, helping to 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.³

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 in real-time based on 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 electronic health records (EHRs) to audio notes and laboratory 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 surpasses that of 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 predict treatment responses and adverse reactions, enabling clinicians to tailor therapies to each patient’s specific 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 offer 24/7 patient support, answering questions, reminding patients about their medications, and alerting providers in the event of abnormal vital signs. This supports proactive health management, particularly for individuals with chronic conditions.

4. Automation of administrative tasks

AI agents manage operations by automating tasks such as scheduling, claims processing, and clinical documentation, as well as other repetitive administrative tasks. This alleviates physician burnout and redirects resources toward care delivery.

5. Enhancing patient experience

AI agents enhance patient interactions with timely and clear responses across various channels, including voice, chat, and text. They offer hyper-personalized care journeys, which reduce wait times and increase patient satisfaction.

6. Drug discovery & clinical trials

AI agents accelerate drug discovery and development by predicting molecular behavior, assessing the likelihood of trial success, and identifying promising compounds.

7. Fraud detection & billing accuracy

AI security agents monitor billing patterns, flag anomalies, and prevent fraudulent claims, ensuring financial integrity and compliance for healthcare providers.

8. Mental health support

Conversational AI offers non-judgmental, anonymous support for individuals dealing with anxiety, depression, or stress. Agents can provide CBT-based interventions or escalate to human clinicians when needed.

Benefits of AI agents in healthcare

Integrating AI agents in healthcare enhances diagnostic accuracy, operational efficiency, and personalized care while reducing administrative burdens:

Improved diagnostic accuracy

AI agents reduce misdiagnoses by identifying subtle anomalies that may go unnoticed during in-person visits.

Operational efficiency

Healthcare systems achieve lower overhead costs by automating documentation, billing, and administrative tasks.

Personalized support

Patient journeys are tailored to individual preferences, needs, and clinical history, enhancing care coordination.

Better access to care

Virtual assistants and multilingual AI agents eliminate language and time barriers, making health services more inclusive.

Reduced administrative burden

Automating prior authorizations, follow-up scheduling, and data entry frees clinicians to focus on care.

Enhanced patient satisfaction

AI improves communication and transparency, providing more trusted, responsive care experiences.

Support for human agents

By offloading routine work, AI agents allow nurses, schedulers, and physicians to devote time to complex care cases.

Emerging trends

Recent advances in AI agents reveal a shift toward continuous monitoring, autonomous decision-making, and hyper-personalized care pathways in healthcare:

• Integration with IoT and wearables: Agents now analyze data from smartwatches, biosensors, and smart implants for continuous monitoring and proactive intervention.
• Agentic AI for complex task execution: AI agents now autonomously handle multi-step tasks, such as verifying identities before resetting passwords or updating medical records.
• Hyper-personalized patient journeys: AI agents dynamically adapt care delivery based on patient behavior, preferences, and health status, guiding patients in a human-like yet scalable way.

Conclusion

AI agents in healthcare are redefining how providers, payers, and patients interact with health systems. These agents are more than tools; they’re collaborators that improve diagnostic accuracy, optimize healthcare operations, reduce administrative overhead, and enhance the patient experience. Their real-world impact spans everything from reducing physician burnout to making care more equitable and proactive.

As healthcare organizations continue to scale AI adoption, the focus will shift from proof-of-concept to delivering measurable outcomes. Intelligent agents working hand-in-hand with human professionals will shape the future of health, ensuring care is more informed, efficient, and patient-centric.

Further reading

• Top 10 Healthcare Analytics Use Cases & Challenges
• Real-Life Applications of Deep Learning in Healthcare
• Chatbots in Healthcare: Insights & Use Cases

External Links

• 1. Virgin Pulse | Cognigy.
• 2. Aveanna Healthcare Improves Employee Experiences with Amelia. Amelia
• 3. Hippocratic AI.