Here’s what we’ll explore together over the next 6 columns.
Column 1 — What’s already here. We begin by naming what’s already on your unit. This article demystifies the tools nurses are already using and makes one matter unmistakably clear: You’re the licensed registered clinician. You’re the legal authority. The tool works for you, not the other way around. And since your patients are likely using AI, too, we’ll talk about what that means for the relationship you’ve worked so hard to build with them.
Column 2 — Reading the alert. The early warning system fires. A risk score appears on your screen. Now what? This article walks through what that number actually means, what a nurse does next, and why the human nursing assessment still determines what happens to that patient—every single time. We’ll also address the questions nurses are quietly asking about privacy, confidentiality, and their own liability when AI is in the loop.
Column 3 — AI and the future of your medication cart. This one goes beyond today’s drug interaction alerts. Pharmacogenomics (personalized medications built around a patient’s own genomic profile) is arriving faster than most of us realize, and AI is driving it. This article helps you understand what your decision support tools are telling you right now and where the science of individualized, genomics-informed medication management is headed. The medication cart of 2030 is already being designed. RNs must be at the table—not just listening, but designing.
Column 4 — When AI makes things up. Yes, AI hallucinates. It can produce answers that sound completely credible yet are completely fabricated—no evidence, no science, just a very confident story. Your patients are reading AI-generated health information right now, today, before they arrive for their appointment. This article gives you a practical framework for separating fact from a very convincing fiction and for helping your patients do the same. As Elphaba reminded us in Wicked: For Good: What people believe to be true and what is actually true are not always the same thing. That gap? Nurses navigate it every day.
Column 5 — Your patient may know more than you think. This one is the flip side of Month 4. Not everything a patient finds through AI is wrong. Some of it is genuinely useful, and some patients arrive better informed than we might expect. This article covers meeting patients where they are and helping them evaluate what they’ve found, connecting them to trustworthy resources, and keeping the therapeutic relationship strong even when the information landscape has become crowded and complicated.
Column 6 — Paid, free, and who’s watching. Open-access journals. Subscription databases. AI tools that cost nothing and ones that cost considerably more. What does a nurse actually need, and what can a nurse access without a university library login? And here’s a question that doesn’t get asked nearly enough: When you use these tools, who’s tracking you? Who owns what you search, what you ask, and what your patients’ data generates?
Roy L. Simpson is a nurse informatician with 5 decades of experience at the intersection of nursing and technology. He’s a professor, co-director, and assistant dean for AI education at the Nell Hodgson Woodruff School of Nursing at Emory University in Atlanta, Georgia.