Volume 23, Issue 4 (Special Issue 2025)
Nursing and Midwifery Journal 2025, 23(4): 1-3 |
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lopez V, Hwang H. The pearls and perils of using AI in nursing practice. Nursing and Midwifery Journal 2025; 23 (4) :1-3
URL: http://unmf.umsu.ac.ir/article-1-5521-en.html
URL: http://unmf.umsu.ac.ir/article-1-5521-en.html
1- School of Nursing and Midwifery, International Institute of Health Sciences, Wattala, Sri Lanka , violeta.lopez@iihsciences.edu.lk
2- School of Nursing, Hubei University of Medicine, Shiyan, Hubei, China
2- School of Nursing, Hubei University of Medicine, Shiyan, Hubei, China
Abstract: (158 Views)
Artificial intelligence (AI) was first conceptualized in 1955 by McCarthy (1956) as the science and engineering of making intelligent machines, especially intelligent computer programs that could do things once done by men. AI uses various forms of computer technology that can learn from data to mimic human capabilities (1, 2). AI is rapidly transforming the nursing profession in delivering care, making clinical decisions, and managing workloads by its presence at the bedside in various forms (3). AI technologies have been reported to enable nurses to provide more evidence-based and individualized care to their patients. Although AI is rapidly transforming nursing practice, there are numerous pearls and perils of using AI in nursing clinical practice, education, and research. These factors need to be considered, and nurses must be aware of when and how to use AI in their day-to-day encounters with patients.
What Are the Pearls of AI in Nursing Practice?
In the clinical context, AI technologies have influenced nurses’ clinical decision-making. For example, wearable AI devices have improved monitoring accuracy, enabling early detection of anomalies and facilitating early interventions.[4] The use of telemedicine was found useful for transmitting real-time health data from rural to urban healthcare settings and for delivering evidence-based interventions to patients with chronic diseases such as diabetes, cardiovascular conditions, and cancer.[5] Nurses also use AI for patient monitoring, risk predictions, individualized care, and clinical decisions (6). In nursing administration, AI-driven automation and predictive staffing capabilities are used to streamline nursing workflows, reduce workload, mitigate burnout, and increase job satisfaction (7). In education, virtual reality and augmented reality platforms can be enhanced through AI. The scoping review by Lifshits and Rosenberg found that AI-based teaching methodology enhanced students’ learning and motivation, and that they felt comfortable and safe when practicing virtual simulations (8). In nursing research, AI-based technologies can be used to examine the effectiveness of patient education delivered via smartphones to patients with chronic diseases at home or to determine the prevalence of falls or pressure injuries among patients.
What are the perils of AI in nursing practice?
AI integration in nursing has several pearls; however, several perils have been reported, including technical issues, ethical dilemmas, and workforce implementation and adaptation. One peril of AI is its lack of robustness, despite many of its successes in different settings (9). The key AI ethical issue is bias and discrimination, especially when implementing AI systems for technical purposes. Over- and under-representation of data may lead to minority bias and discrimination (10). Problems with AI algorithms also raised ethical concerns, as developers and users may not be able to detect errors in data produced or disseminated, compromising patient privacy (11) or (12). These further support Hassan and El-Ashry’s qualitative study, which found that, despite real-time AI data’s potential to strengthen decision-making, an over-reliance on automated alerts risks diminishing nurses’ critical thinking and clinical judgment if not carefully balanced with human oversight (13).
What now for nursing practice
As the current nursing program does not prepare nurses to work with AI technologies, it has been suggested that developing the nursing curriculum should include AI literacy in machine learning principles and nursing competencies (14). Continuing professional education of clinical nurses must also be supported to encourage the adoption of AI technologies in clinical environments. Nurses are being called upon to advocate for the use of AI technologies for nursing practice, the profession, and the patient population (15, 16). Nurses must become active key members of the AI development and implementation team (17) as they have the knowledge of what needs to be integrated in AI-technologies for use in clinical practice. Nurses’ involvement in developing AI-technologies will ensure that they are aligned with clinicians’ values, respect patient dignity, and provide equitable care delivery. El Arab et al. recommend adopting the Nursing AI Integration Roadmap (NAIIR), a structured, ethically informed, user-centred framework, to support the successful integration of AI technologies across all aspects of nursing practice (3). In conclusion, AI technology is not a replacement for nursing critical skills or the compassionate human touch that only a human nurse can deliver.
What Are the Pearls of AI in Nursing Practice?
In the clinical context, AI technologies have influenced nurses’ clinical decision-making. For example, wearable AI devices have improved monitoring accuracy, enabling early detection of anomalies and facilitating early interventions.[4] The use of telemedicine was found useful for transmitting real-time health data from rural to urban healthcare settings and for delivering evidence-based interventions to patients with chronic diseases such as diabetes, cardiovascular conditions, and cancer.[5] Nurses also use AI for patient monitoring, risk predictions, individualized care, and clinical decisions (6). In nursing administration, AI-driven automation and predictive staffing capabilities are used to streamline nursing workflows, reduce workload, mitigate burnout, and increase job satisfaction (7). In education, virtual reality and augmented reality platforms can be enhanced through AI. The scoping review by Lifshits and Rosenberg found that AI-based teaching methodology enhanced students’ learning and motivation, and that they felt comfortable and safe when practicing virtual simulations (8). In nursing research, AI-based technologies can be used to examine the effectiveness of patient education delivered via smartphones to patients with chronic diseases at home or to determine the prevalence of falls or pressure injuries among patients.
What are the perils of AI in nursing practice?
AI integration in nursing has several pearls; however, several perils have been reported, including technical issues, ethical dilemmas, and workforce implementation and adaptation. One peril of AI is its lack of robustness, despite many of its successes in different settings (9). The key AI ethical issue is bias and discrimination, especially when implementing AI systems for technical purposes. Over- and under-representation of data may lead to minority bias and discrimination (10). Problems with AI algorithms also raised ethical concerns, as developers and users may not be able to detect errors in data produced or disseminated, compromising patient privacy (11) or (12). These further support Hassan and El-Ashry’s qualitative study, which found that, despite real-time AI data’s potential to strengthen decision-making, an over-reliance on automated alerts risks diminishing nurses’ critical thinking and clinical judgment if not carefully balanced with human oversight (13).
What now for nursing practice
As the current nursing program does not prepare nurses to work with AI technologies, it has been suggested that developing the nursing curriculum should include AI literacy in machine learning principles and nursing competencies (14). Continuing professional education of clinical nurses must also be supported to encourage the adoption of AI technologies in clinical environments. Nurses are being called upon to advocate for the use of AI technologies for nursing practice, the profession, and the patient population (15, 16). Nurses must become active key members of the AI development and implementation team (17) as they have the knowledge of what needs to be integrated in AI-technologies for use in clinical practice. Nurses’ involvement in developing AI-technologies will ensure that they are aligned with clinicians’ values, respect patient dignity, and provide equitable care delivery. El Arab et al. recommend adopting the Nursing AI Integration Roadmap (NAIIR), a structured, ethically informed, user-centred framework, to support the successful integration of AI technologies across all aspects of nursing practice (3). In conclusion, AI technology is not a replacement for nursing critical skills or the compassionate human touch that only a human nurse can deliver.
Type of Study: Editorial Note |
Subject:
Digital Nursing
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