Trends and Issues in Nursing Informatics Column

By Melanie Neumeier RN MN

Melanie Neumeier is an Assistant Professor in the BScN Program at MacEwan University in Edmonton, Alberta. Her research interests include integrating new technologies into nursing education and interdisciplinary collaboration in enhancing evidence-informed nursing practice. Melanie first became interested in nursing informatics through a nursing informatics course she took in her MN program at Memorial University in Newfoundland, and has since continued that interest in her research, her writing, and her teaching.

Citation: Neumeier, M. (2025). Is it necessary to understand how AI is created in order to effectively use it? Trends and Issues in Nursing Informatics Column. Canadian Journal of Nursing Informatics, 20(3). https://cjni.net/journal/?p=15321

AI is now commonplace in healthcare and is used in all areas of practice from creating clinic notes to patient treatment plans, and everything in between. As nurses we know that AI is something we need to learn how to use. We know that it is important that we enter complete and accurate data into the EMR so that AI treatment algorithms can make the most accurate recommendations for care. We know that using AI effectively is not only an entry to practice competency, but an ethical imperative. So, is it sufficient to be end users of AI, or do we need to know how AI systems actually work? Do we need to know how to create those systems instead of just how best to use them? Some universities think so.

The University of Texas at San Antonio offers a dual degree program combining a Doctor of Medicine with a Master of Science in Artificial Intelligence. Their curriculum is designed for physicians to apply AI in diagnostics, treatment planning, and operational efficiencies in the healthcare system. The University of Toronto has an MD Plus program that enables medical students to pursue dual graduate degrees, including in applied computing and health informatics. Now we are seeing more of these programs being offered at universities throughout North America, and these programs are not just for medicine.

Florida Atlantic University offers combined programs in nursing and artificial intelligence, with the option to continue on to a master’s in biomedical engineering. They also offer a BSN to MS in AI for nurses, structured to accelerate the path to advanced interdisciplinary roles. TECH also offers a Professional Master’s Degree in Artificial Intelligence in Nursing to train nurses in advanced AI competencies for clinical practice, leadership, and digital health innovation. And Carleton is now offering a BScN with a concentration in artificial intelligence aiming to prepare nurses to lead in health data technology.

What these programs signal is a shift in how we view the role of nurses in the digital health ecosystem. It is not only about being competent in using AI-powered tools: it is about having a seat at the table where those tools are designed, critiqued, and refined. Nurses are uniquely positioned as both the largest segment of the healthcare workforce and the clinicians who spend the most time at the bedside. Bringing AI literacy, and in some cases even AI development knowledge, into nursing practice ensures that these technologies are built with patient-centered care and ethical use at the forefront.

For the future of nursing, this blending of clinical and computational expertise may create new roles at the intersection of practice, policy, and technology. Nurse informaticists with AI training could serve as translators between data scientists and clinical teams, ensuring that predictive models reflect real-world patient complexities. Advanced nurses could be leaders in digital health innovation, championing algorithms that address health disparities rather than reinforce them. And for bedside nurses, a broader understanding of AI could bring greater confidence in advocating for whether and how these systems should be applied in patient care.

The question, then, is not only whether nurses need to understand how AI is created, but also what kind of understanding will best serve our profession. For some, end-user proficiency and strong informatics skills will be enough. For others, pursuing advanced training in AI development could open doors to shaping the very systems that are transforming healthcare. Either way, the future of nursing informatics lies in ensuring that nurses are not simply passive adopters of AI but active voices in how it is imagined, implemented, and evaluated.