AI in Nursing Education: The Case for Critical AI Literacy

The Professional Context

The Royal College of Nursing Congress 2025 formally debated the use of artificial intelligence in nurse education, recognising that generative AI is already shaping healthcare practice and that nursing programmes must equip students with the skills to engage with these technologies responsibly. The Dorset Branch submission noted that by closely monitoring AI integration and fostering a positive learning atmosphere, nursing education can equip future nurses to thrive in an increasingly technology-driven healthcare landscape.

This position is echoed by the Council of Deans of Health, whose Innovation Month 2025 blog from student nurse Jake Shaw described how AI tools are already being used by students for literature review, care plan structuring, patient interaction practice, and academic writing support. Shaw observed that universities' cautious adoption of AI in education risks leaving future clinicians underprepared to leverage these tools effectively.

The Literacy Gap

Writing in Nursing Times in November 2025, student editor Romy Duckett argued that nursing education must catch up to the realities of how AI can be used. The article made the case that critical AI literacy — the ability to evaluate, question, and responsibly use AI outputs — should be a core component of modern nursing competence, not an optional extra.

A comprehensive umbrella review published in the Journal of Medical Internet Research (El Arab et al., 2025) synthesised 18 systematic and scoping reviews on AI in nursing education and practice. The review identified three recurring challenges: persistent gaps in ethical oversight of AI tools; the absence of standardised AI literacy programmes in nursing curricula; and the risk that overreliance on AI could erode essential interpersonal and empathy-driven skills.

The JMIR review was explicit: the current nursing education system may not be adequately preparing future nurses to navigate the complexities of AI-integrated environments, necessitating curriculum reform and the development of AI literacy programs.

The Documentation Challenge

One recurring challenge in nursing education is that students are assessed on the quality, structure, and professional coherence of reflective and placement documentation long before they have access to the documentation systems used in clinical practice. This creates a gap between educational expectations and the tools available to students, particularly in relation to structure, formatting, and alignment with professional standards such as the NMC Code, NMC Standards of Proficiency, and the Future Nurse competencies.

Students using general-purpose AI tools such as ChatGPT to help structure placement reflections face specific risks. These tools generate new content, which means they may fabricate clinical observations, hallucinate professional terminology, or introduce language that does not reflect the student's actual experience. In a profession where documentation is both a learning tool and a professional accountability mechanism, this creates a fundamental integrity problem.

Structuring vs Generating: A Critical Distinction

The distinction between AI tools that generate content and tools that structure existing content is particularly relevant in nursing education. Generative tools create new text based on prompts, introducing the risk of fabrication. Structuring tools organise the student's own words into professionally aligned formats without adding, interpreting, or inventing content.

This distinction matters because it preserves the student's professional voice and clinical judgement while providing the structural scaffolding that aligns output with NMC frameworks. The student remains the author. The AI is the organiser.

As the JMIR review noted, the ethical dimensions of AI education require attention, including reflective practices that encourage nurses to balance the technical benefits of AI with the humanistic aspects of care. A structuring approach supports exactly this: it helps students produce professionally formatted documentation while requiring them to provide all clinical content, observations, and reflective analysis themselves.

What This Means for Nurse Educators

The convergence of the RCN Congress debate, the Nursing Times commentary, the Council of Deans perspective, and the JMIR umbrella review points to a clear trajectory: AI literacy will become a required component of nursing education, and institutions that integrate it thoughtfully will produce more digitally capable, critically aware practitioners.

The question is not whether students will use AI tools — they already are. The question is whether educators provide governed, ethically aligned alternatives, or leave students to navigate ungoverned general-purpose tools independently.