Artificial intelligence has officially passed “buzzword” status. It’s here, and we have two options:

1: Allow other professions to take the reigns in AI and its applications in nursing.

2: Be in front of the curve and “nursify” any AI that inevitably infiltrates the nursing profession.

To Jing Wang, PhD, MPH, RN, FAAN, we have only one option. Nurses must take an active role in shaping AI to ensure it enhances the nurse experience and patient care. From starting as a researcher to launching the nation’s first MSN in AI applications in Health Care, learn about Wang’s journey, and how you can join her at the forefront of the AI revolution.

Q: What is your nursing background? 

A: I went straight into research.

I started my undergraduate studies in a medical college in China. It was their first year opening a school of nursing under their medical college. Then, I came to the United States and went to the University of Pittsburgh for their BSN to PhD program and, during the program, I got an MSN focused on clinical research and a Master’s in Public Health. My training was very interdisciplinary, but my primary identity was always a nurse. 

Q: Where did your research career begin?

A: I started my nursing research journey before smartphones, using paper and digital diaries to study how digital self-monitoring can help with weight loss and diabetes control. Since then, I’ve focused on self-monitoring and digital health tools.

I’ve seen the evolution of the digital health field. I studied how consumer technology integrates with electronic health records and nurses' workflows in clinical and home settings, particularly around aging in place. I founded research centers, always with an emphasis on integration, education, and practice.

When COVID hit, suddenly, this became everyone's field. I used to beg hospitals to connect remote monitoring wearables to EHRs. A few years into COVID, everyone was asking me how I did it. This led me to create usability standards for connected technology, helping future EHR systems improve.

Currently, I focus on AI tools and their impact on nursing workflows, particularly ensuring AI doesn’t overwhelm nurses with unnecessary alarms. As the dean of the Florida State University College of Nursing, I helped launch the nation's first master’s program on AI Applications in Health Care. We recently partnered with the Coalition for Health AI to create educational programs for nurses on AI and responsible implementation.

Q: What does the concentration in AI degree entail?

A: The program at Florida State University is a Master of Science in Nursing with a concentration on AI Applications in Health Care. We also launched the Nursing and AI Innovation Consortium, uniting nursing schools, healthcare systems, and the AI industry to develop standards and amplify nursing’s voice in AI.

This MSN degree meets traditional requirements while incorporating AI-focused coursework. Nurses can pursue roles like preceptor or instructor, depending on state criteria. While students won’t be coding AI, the program includes four AI concentration courses.

Q: What are the four concentration courses in nursing AI applications?

A: The four concentrations in nursing AI applications are:

1. Foundational AI Principles: First, students study the foundations of AI applications, focusing on the application cycle, rather than as a developer or engineer. You’ll learn to collaborate in evaluating current AI products and implementing solutions. You’ll need to understand the language surrounding what AI means, such as predictive AI, computer visioning, machine learning, and deep learning. You won’t just say, “Oh, this is a sepsis detection tool,” but you’ll understand how it’s a predictive AI, how it pulls from different data sets, and where its bias is.
2. Ethics and Regulations: This covers AI principles, ethics, and regulations at the state, federal, and industry levels. Nurses will learn how to navigate AI’s impact on clinical decisions, like balancing AI predictions with clinical judgment. For example, if your AI tells you that a patient is low risk for sepsis, but in your experience, you feel the patient is unstable, what is the ethical decision to make when interacting with the AI tool? How do you work with engineers when you experience alarm fatigue?
3. Informatics and AI Integration: This focuses on integrating AI tools with nursing workflows. The goal is to reduce time spent in front of computers and help nurses spend more time with patients.
4. Capstone: A project where students select an AI-related topic and develop a proposal for implementation. You’ll analyze pros, cons, challenges, and solutions to experience real-world AI applications in nursing.

I explain to people that this is very different from nursing informatics, as it prepares nurses with advanced clinical skills while integrating AI tools into the nursing process.

Q: How do we make sure that AI doesn’t become an excuse for hospitals to worsen nursing ratios?

A: We need nurses at the table when implementing an AI solution. We need responsible AI, with the goal of training people to understand what responsible AI implementation looks like. 

There is some advocacy at the national level in developing some assurance standards for AI, in layman’s terms, a “nutrition label.” There also needs to be a clinical team that is constantly evaluating the workflow integration of AI in a governance model. Some AI tools don’t save nurses time, and actually take more of their time. AI integration should be data-driven to ensure safe and effective healthcare delivery. 

Everyone gets in a hype of “let’s do this,” and they might not understand that without a mechanism to continue to evaluate and monitor, you create so many alarms for nurses to pay attention to, and it’s not always accurate and doesn’t always save time. There are good intentions, but AI doesn’t always produce the right outcome in the real world. 

Rapid Fire Round

Q: What book or podcast do you recommend for nurses?

A: Right now, I’m reading Empowering Nurses with Technology: A Practical Guide to Nurse Informatics by Kathleen McGrow, the Chief Nursing Information Officer at Microsoft. 

Q: If you could create your ideal nursing course that doesn’t exist yet, what would it be?

A: I would like to design a digital health AI innovation course for undergraduate students. 

Q: How would you describe the future of nursing in 5 words or less?

A: I came up with a term, “nursifying AI.”

I really believe there is power for nurses to use AI to deliver safe care, to help with patient ratios, to help with burnout, and to help with a lot of pain points I see with nursing. AI has a lot of potential, but not until nurses can own AI and support the opportunities that lie ahead of us. 

Final Thoughts

AI in nursing is not about replacing human judgment. It’s about strengthening it. Wang believes that as nurses get involved with AI creation and integration, nurses can help shape the future of technology that supports both clinical-decision making, and compassionate patient care. 

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