By: Lisiane Pruinelli and Tamara Macieira
What if we told you that within the next few years, every nurse entering the workforce could be equipped with the knowledge, skills and confidence to safely and effectively use artificial intelligence (AI)? Not as a distant dream, but as a direct result of how we design nursing education today.
That’s the vision driving our work at the University of Florida College of Nursing’s AI Subcommittee, and of national and international collaborations like the Nursing and Artificial Intelligence Leadership Collaborative (NAILCollab), and in events such as the 4th Workshop on Artificial Intelligence in Nursing (AINurse25), held in Italy this past June. Each initiative underscores the same imperative: We must build an AI-inclusive curriculum to prepare a future AI-ready nursing workforce.
Since launching FloGatorAI in October 2024, we’ve spotlighted groundbreaking AI applications in clinical care, nursing informatics and health systems. But this month, we shift our focus to something more foundational: Education. Specifically, how do we translate the explosion of AI innovation into nursing programs that are not only responsive but visionary?
Why AI Belongs in Nursing Education
AI is no longer an emerging trend – it’s already transforming how we assess patients, deliver care and manage complex health systems. But if we want to ensure nurses are leading, not just reacting to these changes, we must rethink how we train them from the very beginning.
Our AI Subcommittee has been wrestling with these questions:
- What core competencies do nursing students and nurses need to engage with AI safely, ethically and effectively?
- How can we prepare nursing faculty, many of whom were trained in a pre-AI era, to teach these concepts confidently?
- What curriculum frameworks allow for flexibility, hands-on learning and interprofessional collaboration?
The answers are not simple, but they are coming into focus. We believe nursing education must:
- Integrate AI across domains and courses, not just as a single elective or module.
- Embrace competency-based education, enabling students to demonstrate mastery through real-world application.
- Prioritize interdisciplinary learning, especially with fields like data science, computer engineering, and ethics.
Moving from Vision to Practice: Competencies that Count
At recent gatherings, from the NAILCollab meeting in Switzerland to the AINurse25 this past June in Pavia, Italy,a clear message emerged: AI will shape the future of nursing. But when it comes to translating that vision into practice, many educators and leaders are still asking: Where do we begin?
The truth is, we don’t need more white papers; we need clear, practical pathways to prepare nurses for an AI-integrated world. That is where competency-based education comes in. By focusing on what nurses need to know and do — not just what they need to memorize — we can build curricula that align with real-world demands. That means embedding AI competencies early, consistently and contextually into nursing education.
Here, at the College of Nursing, our AI Subcommittee has begun defining core competencies that reflect how nurses engage with AI: as data contributors and users, ethical decision-makers, clinical collaborators and system and technology innovators. We have taken inspiration from existing frameworks while customizing for nursing-specific use cases. Other groups, like those represented at AINurse25, are doing the same, i.e., building simulation-based content, leveraging real datasets and exploring interprofessional partnerships that put AI fluency into action.
This is not just curriculum reform; it is readiness engineering. We are designing learning experiences that prepare nurses not only to understand AI but to shape and lead its development and use in diverse clinical settings.
What Comes Next
We are not suggesting that every nurse should become a data scientist or an AI expert. But every nurse should understand the systems shaping their workflows, influencing their decisions and impacting patient outcomes.
This requires a shared commitment from nursing programs, health systems, regulatory bodies and yes, industry partners. It also requires us to stop treating AI education as a luxury or afterthought.
Together with colleagues on the AI Subcommittee and national collaborators like NAILCollab, we are developing scalable, inclusive and practice-informed strategies to build this capacity. From prompt engineering guides (e.g., see FloGatorAI Cook Book edition 1 and edition 2) and case-based learning activities to faculty development workshops and cross-disciplinary collaborations, the work is happening here and expanding to other places.
Join Us in Shaping the Future
Whether you are an educator, clinician, student or industry leader, now is the time to act.
The path forward will be messy. It will require trial, error and iteration. But it will also be filled with possibility and excitement.
We invite you to read, share and join the conversation. What does AI-inclusive nursing education look like where you are? What barriers are you facing? And how can we move from isolated initiatives to collective impact?
Let’s design the future, together.