Why Faculty Must Embrace AI in Nursing Education, Starting Now
Using AI to Improve Learning and Outcomes in Nursing Programs
Nursing education and nursing practice are out of sync when it comes to the use of artificial intelligence and other rapidly developing technologies. As a result, nursing students can enter practice facing a steep learning curve.
Dan Weberg, PhD, MHI, BSN, RN, a clinical assistant professor at The Ohio State University and the executive director of nursing workforce development and innovation at Kaiser Permanente, contends that underutilization of technology in nursing education is a disservice to the nursing profession — and ultimately to patient care.
"Technology in general is absent from our healthcare education, and specifically nursing education," he said. “In the clinical space, we’re really good at helping students make decisions based on the physical exam. I'm not saying the physical exam needs to go away — it's a core element in our profession — but it's only one modality that nurses are actually practicing in once they've graduated.”
Why Nursing Programs Must Integrate AI Into Curricula
The traditional physical exam is certainly foundational to nursing, but it is no longer sufficient in isolation, Weberg said. He proposes a more holistic approach, in which nursing students learn to perform assessments using a variety of tools and platforms: video visits, secure messaging, and even social media. Such adjustments would help education reflect the diverse ways nurses interact with patients today.
“As faculty, we can augment our clinical physical exam skills with technology and AI to teach our students to incorporate different modalities to assess a patient. We can also incorporate decision support tools to help students make decisions based on that assessment.”
Weberg said AI is undervalued as a teaching tool within the classroom and during clinicals. He encourages educators to view artificial intelligence as an additional source of evidence and to challenge students to critically analyze AI-generated recommendations.
"We have to teach students to assess what AI comes up with," he said. “Assign students to evaluate AI suggestions against their own knowledge and clinical experience, to arrive at better decisions — similar to how they perform evidence-based practice assessments.”
Shifting the View on Technology From Adjunct To Need
In nursing education, AI and other technologies are not mere adjuncts, but rather core components that help develop and enhance clinical decision-making skills, Weberg said.
“Most of the AI medical tools aren’t free, but you can have students use these tools for free,” he said. “You can create scenarios and as you're creating them, type the answers into Chat GPT to see what comes up. Now you can compare and have that dialogue with your students.”
For academic programs that don’t have financial resources to invest in more advanced AI technology, Weberg said simulating AI is both practical and beneficial. If direct access to AI tools isn’t available, educators can create scenarios that mimic AI input. This method trains students to critically evaluate information and to view AI as one of many factors influencing their clinical decisions. For example, in lieu of an AI resource, a faculty member could act as a clinical decision support tool.
“You can have the students do their assessment and then mock up delivering that information to them, either through voice or something in writing,” he said. “Sometimes you need to make it inaccurate so that the students have to actually critically think.”
Students then consider whether the information provided by the simulated AI resource is worth using. An alternative is to provide accurate information so that it changes the way the students think about the solution. Then provide a solid debriefing.
“Ask them, ‘How did you determine whether this was good or bad information? What experience? What evidence do you have? Does it seem reasonable?’” Weberg said. “You can actually use that evidence-based practice process to assess real-time suggestions from a simulated machine insight. And that alone gets students to stop thinking about AI as the answer and more about another data point to make a decision on.”
Using AI to Assist Faculty in Test Development
In addition to enhancing learning and teaching, AI can be incorporated in the day-to-day tasks of nursing faculty. One of the most efficiency-generating applications of AI is in question writing and test creation — a responsibility that can be challenging and time-consuming for educators.
The struggles associated with assessment creation are widely recognized. A 2022 survey of 300 nurse educators from 44 states found that half did not feel confident in their ability to write NCLEX-style items — even if they had received training in this process (Moran et al, 2022). Respondents who received formal education or training in item writing reported being only somewhat confident (51%), and 49% of respondents who had not received training reported being ambivalent or not confident.
The authors of this study, published in Nurse Educator, determined that writing test questions is a complex and time-consuming process that is particularly challenging for new faculty who haven’t had prior academic training.
Other research has identified a lack of item-writing resources as a potential factor in faculty burnout and turnover. In an unpublished 2023 survey of 795 nurse educators who left academia, 43.3% (n = 345) cited inadequate teaching resources as a contributing factor. In a follow-up question to 208 faculty, 55.8% (n =116) of respondents identified the creation of assessments as a top concern. The survey was conducted by Ascend Learning, the parent company of ATI Nursing Education.
Incorporating AI into platforms that help nursing faculty write test questions can help reduce the time requirements and stresses associated with this important responsibility. The first resource to provide this ability is Custom Assessment Builder with Claire AI™️.
To use this resource, introduced in 2024 by ATI Nursing Education, faculty simply enter prompts to generate questions they can evaluate for inclusion in their assessments. Importantly, the educator is always the final decision maker. After Claire AI generates each question, faculty review and edit it, request revision, or accept it and enter it into an assessment.
Since Claire AI was integrated into Custom Assessment Builder in April 2024, faculty in more than 2,000 nursing programs have used it to generate more than 500,000 questions. In an ATI survey of faculty users conducted in February 2025, the overwhelming majority credited Claire AI with significant time savings in their creation of assessments.
Learn more about CAB with Claire AI in this blog article.
Why Integrating Technology and AI in Nursing Education Is Imperative
Despite the numerous potential benefits of AI in nursing education, Weberg acknowledges that some faculty and programs are hesitant to incorporate a significant amount of digital technology. He cautioned that avoiding today’s rapidly evolving tools could render nurses less prepared for the technological realities of healthcare practice.
"It's fine if you don't want to use AI, that is your choice,” he said. “But that's not going to stop it from being used in the workplaces where new nurses will begin their careers.”
Weberg urges educators to provide students with exposure to AI and other technologies and to explore the evidence-based benefits of AI in improving care and nursing practice.
Beyond the classroom, AI's potential as a decision-support tool in clinical settings is immense, Weberg said. Today’s AI tools can assist nurses in interpreting assessment findings and guide them through clinical decision-making processes — compelling reasons to bring AI into the classroom.
"Using information from AI and some of the decision support pieces,” he said, “we can go into an AI tool like ChatGPT and say, ‘I have this assessment finding … what should I be looking for?’" This provides an interactive learning experience that fosters critical thinking and situational awareness in nursing students, he said.
Some of the available AI decision supports are designed for use in emergency department triage. Weberg described these as a second set of eyes that analyze patient data and prompt nurses to consider potential issues that may not be immediately apparent.
"It's using AI to read the electronic medical record, which is impossible at triage," Weberg said, noting that it illustrates how AI has the potential to support nurses in making more accurate triage decisions.
Weberg believes that the advent of AI calls for a reevaluation of the traditional evidence hierarchy in nursing. A model that embraces real-time data, allowing nurses to make informed decisions based on the most current information available, is needed.
"With AI, we can actually ask real-time questions about what's happening in the moment," he said. This shift will empower nurses to supplement historical evidence with insights drawn from AI, he said, potentially enhancing the quality and timeliness of patient care.
