How Arizona State University Integrates an AI Nurse Assistant into USA Health Care Education
The Role of Agentic AI in Modern Health Care
The integration of artificial intelligence into clinical settings has moved beyond theoretical discussions and into practical application. Across the USA, health care systems are exploring how technology can alleviate administrative burdens and improve patient outcomes. One specific area of development is the use of agentic AI—a type of artificial intelligence capable of taking autonomous actions to achieve specific goals, rather than simply answering static queries. Arizona State University is currently at the forefront of this shift, actively testing an AI nurse assistant designed to support clinical teams and patients alike.
Understanding the distinction between traditional software and agentic AI is critical for modern nursing education. Traditional electronic health record systems require manual data entry and retrieval. An agentic AI nurse assistant, however, can synthesize patient data, anticipate needs, and execute conversational tasks based on the context of a patient’s condition. This capability is becoming increasingly relevant as health care facilities face rising patient volumes and administrative demands.
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Inside the Edson College Evaluation Initiative
At the Edson College of Nursing and Health Innovation, faculty and students are participating in a yearlong evaluation of an AI nurse assistant named Avery, developed by the Arizona-based company Drive Health. This initiative is not a passive demonstration; it is a rigorous academic assessment designed to determine if the AI can serve as a useful, ethical, and trustworthy aid in medical settings.
The evaluation process mirrors the standard nursing education model. Just as students are tested on their clinical knowledge through simulated case studies, Avery is subjected to the same academic rigor. Recently, nursing students participated in a simulated scenario involving a fictional 35-year-old patient, Regina Fields, who presented with an acute kidney injury. The students used the AI nurse assistant via its chatbot function to ask questions about the patient’s symptoms, treatment protocols, and necessary interventions.
This hands-on evaluation allows Arizona State University to gather direct feedback from the nursing students who will eventually work alongside these tools. By integrating the AI into their current coursework, students can critically assess its accuracy, relevance, and limitations in real time.
How the AI Nurse Assistant Operates
To prepare for these evaluations, developers fed Avery the exact same foundational materials that Edson College prelicensure nursing students receive. This includes lecture notes, textbook readings, clinical handouts, and procedural guidelines. The goal is to ensure the AI nurse assistant operates within the established standards of current nursing education.
When a student or clinician interacts with the system, the AI draws upon this ingested knowledge base to generate responses. The evaluation then measures whether these responses are noninferior to the answers provided by human nursing students. If the AI passes these academic and practical benchmarks, it moves closer to receiving a formal seal of approval from the university, which is targeted for the end of 2027.
Addressing the Nursing Shortage in the USA
The development and testing of an AI nurse assistant is fundamentally driven by the persistent staffing crises affecting health care in the USA. According to data from the Baylor College of Medicine, only 16 percent of registered nurses currently practice in rural areas. This severe geographic imbalance leaves many underserved communities without adequate access to medical expertise.
Kevin Longoria, CEO and co-founder of Drive Health, notes that the core thesis behind Avery is the urgent need for actual labor in health care. While the AI cannot replace the physical and empathetic care provided by a human registered nurse, it can provide a consistent presence. The AI nurse assistant is designed to be available 24 hours a day, seven days a week, filling the gaps when human clinicians are unavailable or overwhelmed by high patient ratios.
For rural clinics or understaffed urban hospitals, this means patients have immediate access to a system that can answer basic questions, triage symptoms, and provide evidence-based guidance at any time of day.
Explore our related articles for further reading on the impacts of staffing shortages and technological interventions in rural health care.
Enhancing Nursing Education with AI Literacy
Recognizing that AI is now a permanent fixture in clinical environments, Arizona State University is adjusting its pedagogical approach. This fall, the Edson College will debut a new course specifically focused on AI literacy in nursing. The curriculum is built to equip students with the knowledge, skills, and attitudes required to use AI safely, ethically, and effectively.
Celia Coochwytewa, assistant director of academic operations at the college, emphasizes that the goal is for students to leave the course with confidence in using AI thoughtfully. More importantly, the course teaches students to maintain a healthy skepticism regarding AI outputs. Nursing students must develop the ability to question the information provided by an AI nurse assistant and recognize exactly where human expertise is irreplaceable.
Margaret Calacci, a clinical associate professor in the prelicensure program, reinforces that AI is simply part of health care now. By embedding this reality into nursing education, Arizona State University ensures its graduates are not intimidated by new technologies, but rather prepared to manage and oversee them.
Practical Applications for Patient Discharge and Follow-Up
One of the most immediate use cases for an AI nurse assistant is post-discharge care. Currently, the discharge process in many USA hospitals is inefficient. Patients are often handed several pages of complex medical instructions while they are still distressed, tired, or confused. As Judy Karshmer, dean of the Edson College, points out, patients rarely read these documents.
An AI nurse assistant can radically improve this process. Instead of static paper instructions, the AI can initiate a follow-up call within 24 hours of a patient’s discharge. During this interaction, the system can explain what happened during the hospital stay, what side effects to expect, and how to manage medications. Because the AI has launched in 19 languages—with the capability to expand to more than 70—it can conduct these follow-ups in the patient’s native language, significantly reducing miscommunication.
Furthermore, patients often hesitate to contact their doctor’s office with minor concerns because they do not want to feel like a burden. An AI nurse assistant removes this psychological barrier. If a patient notices unexpected swelling or has a question about a wound, they can interact with the AI to receive immediate, guideline-based feedback. The system can then escalate the issue to a human nurse if the symptoms indicate a serious complication.
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The Future of Human-AI Collaboration in Nursing
The evaluation taking place at Arizona State University highlights a crucial distinction in the modern era of health care: the difference between replacement and augmentation. The AI nurse assistant being tested is not intended to take over the nursing profession. Instead, it is designed to handle time-consuming administrative and communicative tasks, freeing human nurses to focus on critical thinking, patient advocacy, and complex clinical care.
Writing reports, summarizing patient histories, and conducting routine discharge check-ins are necessary tasks, but they do not always require the advanced clinical judgment of a registered nurse. By delegating these responsibilities to an AI system operating under the supervision of a human care team, health care facilities can operate more efficiently and reduce clinician burnout.
As the yearlong evaluation progresses, the feedback from ASU nursing students will be instrumental in shaping the final capabilities of the AI nurse assistant. Their assessments will determine whether the technology can truly be trusted in high-stakes environments. If successful, this collaboration between academia and the technology sector could establish a new standard for how AI is integrated into nursing education and clinical practice across the USA.
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Share your experiences in the comments below if you have interacted with automated systems during a recent medical appointment or hospital stay.
