When I graduated with my BSN in 2003, that hospital felt a world apart from the hospital a new graduate will walk into in 2026. The latter, leaning into futuristic technology, AI systems, robotics, and smart monitoring. It can almost feel “Jetsons-like” when thinking back to early 2000s care. While the characteristics that make a great new nurse – one destined for the job – never change, in my opinion, the job certainly has. With it, nursing education needs to evolve to produce day-one, practice-ready graduates.
An urgent need and opportunity for new nurses
The success of our hospitals hinges on having strong candidates to work on our floors. Today, hospital leaders are struggling to fill open roles. And once filled, they are struggling to keep those candidates. Recent research found that nearly one-quarter of new nurses quit within their first year in the field and one-third quit within two years. These challenges highlight a growing disconnect between traditional curriculum and what it needs to cover now to produce graduates prepared to work with both patients and new technologies.
Educators are seemingly coming around to AI after countless concerns about negative learning impacts and worry about overreliance. OpenAI recently sold more than 700,000 ChatGPT licenses to about 35 public universities for students and faculty – a positive shift, especially for nursing education.
In the classroom, nursing students should be encouraged to engage with experiential learning and AI-enabled tools, including AI documentation support and simulation technologies. These technologies allow students to practice skills in safe, repeatable environments. The earlier students are exposed to real-world technologies, the more likely they are to enter the workforce confident, adaptable, and prepared.
Where workforce expectations meet AI
Hospital and hiring leaders are not expecting new graduates to be AI experts on day one. They do expect them to understand how to work alongside technology safely, confidently, and thoughtfully. The following strategies reflect what hospitals increasingly need from their academic partners as care environments become more technology-enabled.
- Integrate technology thoughtfully: AI is not a colleague, a competitor, or the decision-maker. It is a tool designed to support clinical judgment and proven teaching methods — and it is already a reality in today’s hospitals. When technology is positioned as an enhancement to experiential learning and patient outcomes, rather than a replacement for foundational skills, adoption becomes far easier.
- Invest in tailored training and support: Confidence drives adoption, and that confidence starts in school. Updating curricula to include hands-on exposure to AI and other tools allows new nurses to build familiarity before they ever hit the floor, forming a productive partnership with technology that enhances rather than replaces their work.
- Embed innovation into curriculum and institutional systems: Closing the readiness gap requires more than pilot programs or electives. When AI and other tools are embedded into curricula, workflows, and governance structures, it signals long-term commitment and mirrors how hospitals evaluate meaningful, scalable investments.
- Measure, share, and adapt: Hospitals operate on evidence, and nursing programs should too. Tracking outcomes, gathering feedback, and sharing results builds credibility and momentum while reinforcing the value of preparing a future-ready nursing workforce.
The big picture
The Health Workforce Analysis published by the Health Resources and Services Administration (HRSA) projects a shortage of more than 63,700 full-time registered nurses by 2030. As workforce pressures intensify, preparing nurses to be practice-ready on day one is no longer optional, and that preparation must begin in the classroom.
Early experience and comfort with AI benefits everyone. Nurses who understand how to work alongside technology are better equipped to deliver high-quality care, adapt to new systems, and navigate increasingly complex clinical environments.
This is a call to build AI and technology confidence as early as possible. When students gain meaningful exposure early, they form a productive partnership with technology that enhances clinical judgment rather than replacing it. Continuing to rely solely on traditional, and increasingly outdated, educational pathways risks leaving new graduates underprepared for the realities of modern care. Embracing AI thoughtfully is not about chasing innovation for its own sake; it is about ensuring the next generation of nurses can thrive in a rapidly evolving healthcare system.
Photo: CASEZY, Getty Images
Dr. Christine “Christy” Heid, PhD, MSN/Ed, RN, CNE, CHSE, is a Nursing Simulation Specialist at UbiSim with more than 20 years of experience in nursing education, simulation, curriculum development, and clinical practice. She created the Heid ATE Guide for Clinical Teaching and Learning and has published on online and simulation-based learning. Dr. Heid has served as a nursing education consultant, principal investigator of a multi-site research study, course coordinator, and clinical faculty, contributing to national organizations including INACSL, SSH, Sigma and OADN. She leverages her clinical, academic, and research expertise to advance simulation-based learning, nursing education, and improved healthcare outcomes for students, faculty, and patients.
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