Early engagement by nurses as a strategy to fairly advance technology solutions
For decades, nurse staffing has been a source of nursing dissatisfaction. It continues to be at the crux of many pervasive issues that impact the sustainability and strength of our profession. There are two opposing views: one narrative describes a shortage of nurses while the other argues a sufficient number of nurses but not enough who are willing to work in current healthcare conditions. The most recent research from the NSI National Health Care Retention & RN Staffing Report indicates that nursing turnover is increasing while retention continues to drop with many nurses reporting their intention to leave the workforce due to decreasing job satisfaction.
The American Nurses Association (ANA) has been at the forefront of tackling issues related to nurse staffing. From publishing ANA Principles for Nurse Staffing in 1999, to more recently convening national work groups to develop the 2021 “Nurse Staffing Think Tank: Priority topics and recommendations” and then the 2022 “Nurse Staffing Task Force imperatives, recommendations, and actions,” ANA has led the national conversation. These publications directly resulted in the inclusion of nurse staffing as a high priority patient safety issue and explicitly described in the 2026 National Performance Goals by the Joint Commission.
Now, nurse staffing is spilling into discussions among the general public. Nursing strikes, conferences, summits, roundtables, and policy discussions around the country list nurse staffing as a critical concern with no end in sight.
As these discussions are happening, the intersection of staffing and equity can’t be forgotten. Although much has been much published about “appropriate” staffing, it’s time to call for nurse staffing to be seen as an equity issue. Equity isn’t just a topic of race and ethnicity. Equity, as McGill University defines it, “denotes fairness and justice in process and in results. Equitable outcomes often require differential treatment and resource redistribution to achieve a level playing field among all individuals and communities.”
Timeline of ANA’s nurse staffing initiatives
- 1999
ANA Principles for Nurse Staffing released. - 2012
Second edition published with expanded guidance around complexity, patient acuity, and workforce factors. - 2015
ANA published the white paper, Optimal Nurse Staffing to Improve Quality of Care and Patient Outcomes, strengthening the evidence base connecting staffing to patient safety and outcomes. - 2019
Third edition of ANA Principles for Nurse Staffing emphasized staffing across all settings, not just hospitals, and linked staffing to nurse well-being, patient safety, and organizational outcomes. - 2023
ANA publicly announced support for federal minimum nurse-to-patient ratio legislation (Nurse Staffing Standards for Hospital Patient Safety and Quality Care Act), marking a stronger position on national staffing standards. - 2026
Through the efforts of a national nurse staffing think tank and task force, nurse staffing is a Joint Commission national performance goal.
Nurse staffing and equitable patient care
Advancing equity in care delivery is a mainstay action and goal in nursing practice, which is centered in our Code of Ethics for Nurses (Code). Equitable nurse staffing acts as a gateway to advancing equity in the communities we serve. It’s impossible for systems to advance equity without ensuring fairness for the nurses who must deliver fair and just care.
Inequitable staffing begets inequitable care—plain and simple.
Inequity presents as differences in the quality of healthcare received by individuals or groups that aren’t explained by clinical need, patient preferences, or appropriateness of intervention; instead, they’re driven by systemic, structural, or interpersonal factors within the healthcare system. The hard lessons on how to meaningfully address inequities start with intra-system introspection to fully understand how systems themselves reproduce inequities for the people who work within those systems. In other words, inequities aren’t solely a patient care issue—they’re a systems issue that impacts numerous people relied upon for the continuity and performance of these systems.
Definitions of appropriate staffing and equitable staffing
Appropriate staffing. A dynamic process that aligns the number of nurses, their workload, expertise, and resources with patient needs to achieve quality patient outcomes within a healthy work environment.
Equitable staffing. Ensures that workload, risk, and resources are distributed fairly, so that care quality and nurse well-being do not depend on patient demographics, unit assignment, or structural disadvantage.
AI in nursing
The evolving landscape of healthcare has been increasingly reliant on technology. The National Institute of Biomedical Imaging and Bioengineering defines artificial intelligence (AI) as an umbrella term that encompasses technology that learns with experience and gains proficiencies beyond its original human inputs. In healthcare, AI includes existing, emerging, and future innovations, much of it with the purpose of supporting clinical practice and patient care, noted by ANA in the position statement, “The ethical use of artificial intelligence in nursing practice.”
The 2025-2026 Nursing Trends Survey, published in American Nurse Journal, showed nurses’ conflicted feelings about AI in the workplace. With over 1,000 respondents to the survey, 76% answered that “AI might or will be helpful in healthcare.” However, nearly 1 in 5 nurses (19%) responded that AI shouldn’t be used in patient care at all. Common concerns included questions about AI’s accuracy, patient safety issues, and the lack of human interaction. However, when asked to identify areas where AI could be helpful, 39% of nurses selected “staffing/scheduling.”
In the recently published “Artificial intelligence (AI) in nursing practice: Consensus findings from the ANA AI in Nursing Practice Think Tank,” equity along with ethics and patient safety are identified as essential to foundational principles for AI use. Current material risks include algorithmic bias, data quality, and lack of transparency, which could lead to patient harm and potentially exacerbate health disparities. (See related article, “Nurses leading AI,”)
AI and equitable nurse staffing
The 2025-2026 Nursing Trends Survey also highlights the convergence of persistent staffing shortages, turnover, and burnout with ethical concerns regarding fairness, transparency, human connection, and trust. According to AAMC, current staffing approaches rely heavily on human factors and may result in inequities, bias, and dissatisfaction among nursing staff. This erosion of confidence may lead to increased moral distress, reduced job satisfaction, and a heightened intent to leave the workplace or nursing profession. AI has the potential to offer a data-driven solution to nurse staffing and workforce building challenges. AI solutions, according to Nashwan and Abujaber, can match patient needs with nursing expertise, optimize patient outcomes, improve processes, and decrease staff burnout.
As healthcare systems introduce technological solutions and embed AI into workforce decision making, the opportunities and ethical risks for each solution must be evaluated through governance rooted in nursing professional ethics and values. Based on areas of consensus, participants in the ANA AI Think Tank identified the following five priority actions for the profession:
- Issue clear, nurse-led guardrails for AI in nursing practice.
- Curate a nursing AI playbook as an implementation-focused resource across practice, education, research, and regulation.
- Advance AI literacy and competence.
- Strengthen policy and regulatory advocacy to advance and elevate the nursing perspective.
- Sustain cross-section collaboration.
In short, nurses have identified staffing and equity as two topics linked closely to AI use in healthcare. (Read more in the consensus summary at bit.ly/4nTtW0b.)
One group exploring the impact of AI on nursing is ANA\California, which established the Advocacy Institute Fellowship to develop nurses’ advocacy skills and knowledge to impact legislation and health policy that focuses on significant issues in healthcare. The ANA\California Advocacy Institute Fellowship has five active campaigns: racism in nursing, media policy, veterans health, AI and documentation/charting, and AI and equitable nurse staffing. The AI and equitable nurse staffing campaign aims to create a framework and state policy recommendations to guide and influence the use of AI in nurse staffing (bit.ly/4ad9G41).
Leading this work, Jethrone Role, DNP, RN, LHIT, 2025 ANA\California Advocacy Institute Fellow on AI and equitable nurse staffing, identified three key focus areas where AI may enable fairer staffing. These include hiring—matching nurse candidates to potential roles based on skills (or competencies) and experience; scheduling—balancing organizational needs with nurse preferences; and patient assignments—distributing acuity and workload more evenly.
While potentially transformational, AI strategies will require commitment to measuring and monitoring ethical risks through robust governance structures and accountability—decreased administrative burden can’t be the sole measurement of success. Role describes how ethical oversight grounded in organizational justice is essential to equitably implement AI-enabled tools in nurse staffing, highlighting the following four ethical dimensions that impact both actual and perceived staffing inequity for nurses:
- Distributive justice—fair allocation of shifts, workload, and opportunities
- Procedural justice—transparent and consistent decision-making processes
- Interpersonal justice—respect and dignity in how decisions are implemented
- Informational justice—clear expectations and opportunities to question decisions
Continuing the work of Role, 2026 ANA\California Advocacy Institute Fellows Sotera Delos Santos, DNP, RN, NEA-BC, CPHQ; Adrienne M. McIntyre, DNP, RNC-NIC, CNS; and Sarah K. Wells, MSN, RN, CEN, CNL, are engaging with nurse leaders and AI industry experts. They’re also gathering data to evaluate how AI staffing tools are used in current practice and their possible impacts on equitable nurse staffing. Further exploration of vetting, acquiring, or implementing AI technologies in the healthcare space, particularly related to equitable staffing, will remain an emphasis of the fellows as they develop advocacy recommendations.
Moving forward: Ensuring staffing equity
There are no easy paths forward. Leveraging AI for equitable nurse staffing will take intention and effort for leaders and organizations. To best promote equitable nurse staffing supported by AI technologies, Role recommends developing nurse-centered assessment tools, evaluating staffing systems, providing recurring educational webinars and workshops, creating outcome measurement frameworks, collaborating with technology vendors, implementing safeguards across the lifecycle of AI products, continually validating AI tools, and conducting further research into AI and equitable nurse staffing. (See Recommendations to promote equitable nurse staffing.)
Harnessing The Power of Nurses
The future of AI as it intersects with staffing requires nurse involvement. Nurses must be part of selection, design, and implementation of AI throughout healthcare. The Code compels nurses, both morally and professionally, to operationalize practices that further health equity. This means integrating equity principles into all AI builds to mitigate bias and combat inequities in patient care.
Further, policy and legislation related to the use of AI in nurse staffing and workforce development must be informed by nurses and built upon equity principles. As AI shifts nurse staffing practices and processes, nurses can guide leaders, healthcare organizations, AI industry partners, and policymakers towards health equity in the future.
ANA\California report recommendations for equitable nurse staffing
Develop nurse-centered assessment tools
- Design tools that capture nurses’ feedback on staffing processes, perceptions of fairness, and allocation of workloads.
- Integrate tools into work routines.
- Use feedback to shape staffing decisions.
Evaluate staffing systems
- Routinely complete reviews of hiring, scheduling, and patient assignment processes to evaluate if they support or mitigate equity in staffing.
Educational webinars and workshops
- Hold regular educational interventions, such as webinars, workshops, and just-in-time trainings, with a focus on topics including ethics and AI, technology, and health equity.
Create frameworks for outcome measurement
- Establish metrics that evaluate how AI tools and technology affect equity.
Partner with technology vendors
- Co-design AI staffing tools as a partnership between nurses and companies to ensure inclusion of equity principles in the design and build.
Implement safeguards
- Implement safeguards to align AI technologies with nursing values, increase equity, foster inclusivity, and remain explainable to users.
Validate AI tools continuously
- Continually validate AI tools using their data to authenticate the promotion of equitable nurse staffing.
Conduct research on AI and equitable nurse staffing
- Conduct ongoing research and use results to inform system improvement, policies and procedures, and future staffing practice innovations.
Source: ANA\California Advocacy Institute preliminary report
— Sarah K. Wells is the founder and innovator at New Thing Nurse. Adrienne M. McIntyre is the president and founder of Adrienne McIntyre Consulting, LLC. Katie Boston-Leary is senior vice president of equity & engagement at the American Nurses Enterprise.
American Nurse Journal. 2026; 21(7). Doi: 10.51256/ANJ072634
References
American Nurses Association. ANA’s Principles for Nurse Staffing. 3rd ed. September 2019. cdn2.hubspot.net/hubfs/4850206/PNS3E_ePDF.pdf
American Nurses Association. Code of Ethics for Nurses. 2025. codeofethics.ana.org/provisions
American Nurses Association. Position statement: The ethical use of artificial intelligence in nursing practice. 2022. nursingworld.org/globalassets/practiceandpolicy/nursing-excellence/ana-position-statements/the-ethical-use-of-artificial-intelligence-in-nursing-practice_bod-approved-12_20_22.pdf
American Nurses Enterprise Artificial Intelligence (AI) in Nursing Practice: Consensus Findings from the ANA AI in Nursing Think Tank. brand.ana.org. Published April 2026. Accessed May 4, 2026. brand.ana.org/s/2wrfjrh9xqm7bk67mmgfgspn
ANA California. Class of 2026 – Advocacy Institute Fellowship. August 26, 2025. anacalifornia.org/post/class-of-2026-advocacy-institute-fellowship
Gilmartin DJ, Saver C. 2025-2026 Trends Survey. Am Nurse J. 2026;21(4):13-8. doi:10.51256/ANJ042613 https://www.myamericannurse.com/2025-2026-trends-survey/
Joint Commission. National performance goal #12: Health professional resource management. 2026. jointcommission.org/en-us/standards/national-performance-goals/health-professional-resource-management
McGill University. Equity. mcgill.ca/equity/resources/definitions
Nashwan AJ, Abujaber AA. Nursing in the artificial intelligence (AI) era: Optimizing staffing for tomorrow. Cureus. 2023;15(10):e47275. doi:10.7759/cureus.47275.
National Institute of Biomedical Imaging and Bioengineering. Artificial intelligence. March 2025. nibib.nih.gov/science-education/science-topics/artificial-intelligence-ai
Nurse Staffing Task Force. Nurse Staffing Task Force imperatives, recommendations, and actions. 2023.
NSI Nursing Solutions, Inc. 2026 NSI National Health Care Retention & RN Staffing Report. March 2026.
nsinursingsolutions.com/documents/library/nsi_national_health_care_retention_report.pdf
Partners for Nurse Staffing Think Tank. Nurse Staffing Think Tank: Priority topics and recommendations. 2022. nursingworld.org/globalassets/practiceandpolicy/nurse-staffing/nurse-staffing-think-tank-recommendation.pdf
Role J. The impact of AI on equitable staffing: Preliminary report. ANA California. October 2025. anacalifornia.org/post/the-impact-of-ai-on-equitable-staffing-preliminary-report
Richter R, Best J. Unequal treatment. 2026. AAMC. aamc.org/professional-development/affinity-groups/gia/awards/unequal-treatment-ruthann-richter-and-jessica-best
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