Learn about AI + nurse hiring...
By: Sarah K. Wells MSN RN CEN CNL
Artificial intelligence (AI) is quietly reshaping how nurses get hired, and not always in ways that are obvious to applicants or even hiring managers.
At its core, AI is now embedded in many applicant tracking systems (ATS) used by healthcare organizations. These systems screen resumes, rank candidates, and sometimes even recommend who should move forward in the hiring process. For nurse applicants, this means your resume may be evaluated by an algorithm before a human ever sees it.
The upside?
AI can streamline hiring in a workforce-strained environment. Recruiters can review larger applicant pools faster, identify candidates with specific certifications or experience (like ICU, ED, or specialty credentials), and reduce time-to-hire >> something critical when staffing shortages impact patient care.
But there’s a catch…
AI systems are only as good as the data and rules they’re built on. If poorly designed or unmonitored, they can unintentionally filter out strong candidates. For example, nurses with non-traditional career paths, career gaps, or international experience may be overlooked if their resumes don’t match exact keyword criteria. This creates a real risk of reinforcing bias rather than reducing it.
For nurses, this shift demands a more strategic approach:
Use clear, standard clinical terminology (think: “Emergency Department RN” instead of creative variations)
Mirror keywords from job descriptions
Keep formatting simple and ATS-friendly (e.g. no images, white background, avoid tables)
Highlight measurable outcomes and certifications
AI vs AI
Applicants are trending to using AI to optimize their resumes. This creates an AI-enhanced resume vs the AI-enabled ATS.
If you’re leveraging AI tools to improve your resume, results come down to how you prompt it (AKA what you tell it to do). Vague asks like “fix my resume” lead to generic edits. Strong prompts are specific, strategic, and tied to a real job description.
Start by pairing your resume with the job posting and asking for alignment. This ensures your experience reflects what employers, and ATS systems, are actually scanning for.
Next, identify gaps. Have AI extract keywords, required skills, and preferred qualifications, then compare them to your resume. This step often reveals what’s missing and where to focus.
Refine key sections. Your professional summary should be concise and role-specific. Your experience should emphasize impact, using action verbs and measurable outcomes when possible.
If your background isn’t a direct match, use AI to translate your experience. This is especially helpful for new grads or nurses changing specialties.
Also run an ATS check. Formatting issues, like columns or graphics, can prevent your resume from being read correctly.
Finally, iterate. Ask for feedback from a recruiter’s perspective and refine accordingly.
Used intentionally, AI helps nurses align their experience with hiring expectations and stand out in a competitive market.
Nurse Leaders + Healthcare Organizations
For nurse leaders and organizations, the responsibility is bigger. AI should support, not replace, clinical judgment in hiring. That means regularly auditing hiring tools, ensuring transparency, and involving nurses in the design and evaluation of these systems.
AI isn’t going anywhere. The real question is whether we use it to create faster hiring or fairer hiring. In nursing, where workforce equity and patient outcomes are tightly linked, that distinction matters.
New Thing Nurse is addressing the problem.
Sarah K. Wells, the founder of New Thing Nurse, is serving as a 2026 ANA-California Advocacy Institute Fellow, focusing on AI and equitable staffing. Working with Dr. Adrienne McIntyre and Dr. Sotera Delos Santos, Sarah is conducting a survey that explores how AI tools are used in hiring, staffing, scheduling, and patient assignment decisions across healthcare organizations. Insights will help inform policy recommendations that support responsible AI use, strengthen nursing oversight, and promote equitable workforce practices.
Sarah and her colleagues are working to contribute to a framework and policy recommendations that address the use of AI in equitable staffing models, grounded in organizational justice and fairness, and will ultimately co-host a panel discussion with nursing and healthcare leaders to share insights and facilitate conversation on equitable staffing models supported by AI in late 2026.
About the Author: Sarah K. Wells, MSN, RN, CEN, CNL is an experienced nurse career strategist dedicated to helping nurses and nurse practitioners of all experience levels and specialties achieve success in their nursing and NP journeys. Sarah founded New Thing Nurse and NTN Consults to help provide support and guidance to the nursing and healthcare community in a simple and direct format. Sarah’s vision is to foster a more supportive and fulfilled nursing world that spreads throughout healthcare and beyond.
Sarah is serving as a 2026 Advocacy Fellow with ANA-California, focusing on AI and equitable nurse staffing. Learn more about the 2026 ANA-California Advocacy Fellowships.
New Thing Nurse helps the nursing and NP community thrive in their careers! Join us on IG or Facebook @newthingnurse 🩺