A Guide to AI and Technology in Nursing Education
Artificial intelligence (AI) is influencing how some nurses monitor patients, record their care, and reach clinical decisions. A McKinsey & Co. survey found that over three-quarters of front-line nurses use AI in their daily work, but to different degrees. Only 10% of nurses are considered “superusers.” The report states that whether or not nurses increase their level of AI use will depend on how healthcare organizations reshape the way nurses do their jobs, end to end.
Many healthcare organizations are expecting that an increase in the use of AI in nursing education will help usher in the next era of nursing practice. The American Academy of Nursing has stressed the importance of AI in healthcare and of nurses increasing their understanding of how to use AI safely and responsibly.
In response, nursing schools are incorporating AI-powered simulation technology, adaptive learning tools, and other digital technologies into their classrooms. At the same time, educators are also considering questions about academic integrity, privacy, bias, and the proper role of human judgment when using AI.
How Is AI Used in Nursing Education?
Nursing education programs are getting students ready to use AI by familiarizing them with the tools they might encounter in hospitals, clinics, and other healthcare environments. Tools used in nursing education range from virtual patients and adaptive learning platforms to AI tutoring systems and predictive analytics tools.
The following sections provide an overview of some of the most commonly used AI tools in nursing education.
AI-Based Virtual Patients and Simulations
Nursing students can acquire clinical experience and skills without working directly with patients in modern clinical skills laboratories. AI extends these opportunities by creating virtual patients that respond to what students say or type.
A study in Clinical Simulation in Nursing showed that experience with AI-based virtual human simulation technology helped nursing students communicate better with older patients, and enabled them to build their empathy, critical thinking skills, and communication skills. These tools can help nursing students practice taking a patient’s history, explaining treatments, responding to concerns, and communicating with other healthcare professionals.
A review published in the Journal of Professional Nursing that examined AI-based technology used for teaching communication skills to nursing students highlights the effectiveness of using virtual simulation technology in nursing education:
In one study, over 90% of students said an AI-powered virtual doctor was engaging and supported their learning.
The average scores on a communication knowledge test rose from 4.22 to 5.59 as a result of the training.
Nursing interns who used an AI virtual patient to take patients’ histories did better than those in the comparison group.
Adaptive Learning Platforms and AI Tutors
The National League for Nursing (NLN), which advocates teaching AI literacy in nursing education, describes several ways AI can enhance nursing education. Examples include the following:
Adaptive learning platforms can provide visibility into how nursing students perform and then adjust the course material to align with each student’s specific requirements.
AI tutoring systems can offer explanations and provide instant feedback, which enables students to spot gaps in their understanding before an exam or before their clinical experience.
Predictive analytics tools can allow educators to detect patterns that can indicate that a student is starting to fall behind, helping them find opportunities to provide these students with support at an earlier stage.
Preparing Students for Clinical AI Tools
Using AI tools in nursing education programs enables students to learn how to use modern clinical systems. It can help them build AI skills that can enable them to advance in their nursing practice and help them prepare for real-world AI use outside the classroom. Clinical AI systems can be employed for tasks that include the following:
Monitoring patients in real time
Identifying changes in patients’ vital signs
Estimating patients’ risk of illness, injury, or disease
Assisting in clinical decision-making
Reviewing large amounts of patient data
Automating parts of clinical documentation
Nursing students should also learn how to evaluate AI-generated information, recognize its limitations, and apply their own clinical judgment to every situation. Simulation tools can give students opportunities to practice making decisions and help them build their skills in a controlled environment.
Other Technology in Nursing Education
AI can help nurse educators teach more effectively and help students learn more deeply. Still, AI is only one type of modern nursing education technology. Other technology in nursing education is used to assist in instruction and ready students for today’s healthcare facilities. These types of technology include the following.
Virtual Reality and Immersive Simulation
Before AI existed, nursing education programs already included virtual reality (VR) and immersive simulation technology. Traditional versions of these tools usually make use of high-fidelity manikins and specially designed laboratories. Virtual reality technology can place nursing students in computer-generated clinical environments where they can practice making decisions and carrying out procedures without putting patients at risk.
Research on the effectiveness of using simulations in nursing education suggests that VR can provide realistic practice for students and help them prepare for real-world clinical situations. Students may assess patients, monitor changes in their condition, and select appropriate nursing interventions as a scenario develops.
Head-mounted displays can make these simulations more immersive by allowing students to interact with a three-dimensional clinical environment rather than simply viewing information on a standard screen. Faculty can then use students’ actions and decisions during the simulation as part of their debriefing process.
Online and Hybrid Degree Programs
Online education programs are a well-established component of nursing education, especially for registered nurses who are going back to school while they continue to work. In a review about online nursing degree programs published in the journal Nurse Education Today, students identified advantages of online education, including the following:
Opportunities for professional advancement
Flexible schedules
Access for students in both rural and urban areas
The ability to continue working while earning a degree
Support from responsive faculty
Telehealth and Remote Monitoring
Telehealth is a significant component of nursing practice and education. Research on telehealth education shows that nursing programs use approaches such as online modules, simulation scenarios, standardized patients, telehealth clinical rotations, and videoconferencing exercises to help students build their digital nursing skills.
Many nurses today use telehealth technologies to communicate with patients who are not in traditional healthcare facilities and monitor their health information remotely. Students, therefore, need experience with telehealth communication, remote assessment, and digital monitoring tools before entering nursing practice.
Telehealth simulations can help students develop skills in these areas by allowing them to practice in realistic patient care situations. As healthcare organizations continue to extend the services they provide beyond hospitals and clinics, these skills may become increasingly relevant.
Benefits of AI and Technology in Nursing Education
The benefits that AI and technology can bring to nursing education apply not only to students and teachers but also to patients. Although research in this field is still limited, existing findings point to several areas where technology can benefit students pursuing nursing education.
A Safer Place to Make Mistakes
Simulations provide nursing students with a controlled setting in which they can practice their skills, make mistakes, and try different approaches without putting any patients at risk. Students can repeat scenarios, receive feedback, and build their communication and decision-making skills before applying them in real-world clinical settings.
Faster Feedback and Stronger Confidence
AI-enabled simulation technology can provide immediate feedback to nursing students and allow them to repeat scenarios as often as needed. This added practice can help students identify their weaknesses, improve their responses, and build their confidence before working with patients.
More Personalized Learning
Every student learns at a different pace. Adaptive learning platforms can identify areas where a student needs more help and provide them with additional practice. Students who have already mastered a topic can move ahead rather than repeat material they understand.
Preparation for Technology-Driven Care
AI and other digital tools are becoming more common in healthcare facilities, so nursing students need to understand how to work with them. Learning the limits of AI technology can help prepare students to use it safely and responsibly in practice.
Tips for Incorporating AI and Technology into Nursing Education
To ensure that their nursing students use all technology effectively and safely, nursing schools need to prioritize thoughtful policies, appropriate educator training, good infrastructure, and clear expectations for students.
The following strategies can be employed by nursing schools to ensure their efforts to integrate technology and AI into nursing education lead to successful outcomes.
Set Clear AI Policies
It is necessary for both students and educators to know whether or not the use of AI is allowed in a particular situation. Nursing education programs can help reduce confusion by:
Defining acceptable and unacceptable AI use
Making academic integrity policies easy to locate
Requiring students to disclose their AI use when appropriate
Establishing a consistent process for reviewing suspected misuse of AI
Explaining the consequences of submitting inaccurate or fabricated AI-generated information
The policies should also make a distinction between using AI as a tool for learning and letting AI take the place of the student’s own reasoning.
Invest in Professional Development
Educators should learn how AI systems work to be able to teach their students effectively. A lack of confidence on the part of an educator and their insufficient technical knowledge can act as barriers to students becoming comfortable with technology.
Professional development opportunities can be provided to educators, such as attending workshops, pursuing further education, acquiring relevant credentials, and working alongside nurses with strong AI and technology skills, as well as professionals in data science, informatics, and ethics.
Rethink How Learning Is Assessed
The proliferation of generative AI tools is making it difficult for educators to be able to tell how much of a nursing student’s work on traditional take-home essays is the result of the student’s own reasoning. Current AI detection software cannot completely resolve this issue, as it provides both false positives and false negatives.
Nursing programs can place more emphasis on assessments that reveal how students think, such as real-world clinical scenarios, case analyses, and oral explanations, rather than written assignments. Such methods can enable educators to judge whether students understand the material rather than merely whether they can give a polished answer.
Plan for Infrastructure, Governance, and Partnerships
Before introducing new digital tools on a large scale, nursing schools must ensure they have reliable networks, compatible devices, cybersecurity protections, and technical support available. The use of AI in nursing education programs also requires that nursing schools create formal AI governance, strategic planning, and data-management policies.
AI in Nursing Education Resources
The following organizations and publications provide additional information on AI in nursing education and the use of technology in clinical practice:
American Academy of Nursing, American Academy of Nursing Statement on Artificial Intelligence in Health Care: An overview of AI literacy, nursing oversight, and principles for responsible AI use in healthcare
American Association of Critical-Care Nurses, “Getting Comfortable With AI in Nursing: An Essential Guide”: An overview on how nurses may encounter and evaluate AI in practice
American Nurse, “Nursing Education, AI, and Best Practices”: A discussion on ways nursing programs can prepare students to work with AI and related technologies
Evidence-Based Nursing, “Embracing Artificial Intelligence in Nursing Education: Preparing Future Nurses for a Technologically Advanced Healthcare Landscape”: A discussion about the need to integrate AI into nursing education curricula so students are prepared to use it responsibly in today’s technology-driven healthcare settings
Nursing Outlook, “N.U.R.S.E.S. Embracing Artificial Intelligence: A Guide to Artificial Intelligence Literacy for the Nursing Profession”: An overview of the NURSES framework, which helps nurses build AI literacy and use AI thoughtfully, ethically, and safely in nursing practice, education, and research
OJIN: The Online Journal of Issues in Nursing, “Advancing Nursing Practice Through Artificial Intelligence: Unlocking Its Transformative Impact”: An exploration of how AI and digital technologies may affect nursing practice and emerging roles
Sage Open Nursing, “Transforming Nursing Education With Artificial Intelligence: A Systematic Review (2010–2025)”: An overview of AI in nursing education studies on personalized learning, simulation, automated feedback, and predictive analytics
Teaching and Learning in Nursing, “Nursing Students’ AI Literacy and Ethical Understanding of AI in Nursing Education”: A report on findings regarding students’ awareness, AI literacy, and attitudes toward formal AI education
AI and the Future of Nursing Education
AI and digital tools in accelerated nursing education programs are impacting the way that nursing students learn and prepare to provide high-quality clinical care to patients. The use of virtual patients, adaptive learning systems, and immersive simulations offers further opportunities for practice, while online education and telehealth training can expand students’ access to nursing education and provide them with more flexibility.
Healthcare partnerships can help enhance these initiatives. Hospitals and health systems can assist nursing programs in identifying which technologies students are likely to encounter and provide opportunities for students to practice using them in real-world settings.
Issues related to academic integrity, privacy, bias, access, and the need for appropriate human supervision remain critical to successfully using AI in nursing education. It is becoming clearer that nurses will need not only clinical expertise but also the ability to carefully assess the technology available to them. By incorporating AI into nursing education programs, nursing schools can enable their students to develop these skills while recognizing that AI is a tool that supports their learning and decision-making rather than one that replaces their professional judgment.
