The Nurse's Role in Generative AI-Assisted Clinical Decision Support Systems The use of Artificial Intelligence (AI) in the health care system is complex and constantly evolving. AI Clinical Decision Support (CDS) systems can help nurses and clinicians with diagnosis, detection of patient deterioration, and optimization of workload and documentation. With the integration of these systems in care delivery, many challenges arise, such as the correct boundaries for the limits of machine intelligence and the continued importance of clinical judgment. The rapidly growing and fluid nature of AI creates the need for a more critical- thinking and informed nursing workforce. This paper will outline how an AI CDS system operates and how it might be used in the nursing field, the ethical issues surrounding algorithms and autonomy and responsibility, and the impact on nurse workload and patient outcomes.
The role of the nurse in interpreting the use of AI Clinical Decision Support Tools
AI clinical decision support systems rely on machine learning algorithms to examine historical clinical data in order to detect patterns. These algorithms run huge volumes of patient data, such as vital signs, lab results, medication histories, and even health records. They alert in real-time, calculate risk stratification, and give suggestions to physicians and nurses on what they should do. In nursing, AI assists in making clinical decisions, employing predictive analysis, and automating documentation. The nurses are the main users and the largest contributors to the system (Brydges, 2025). Nurses are integrating AI systems at different points in their service delivery, such as AI systems that can alert them to patients in critical conditions during initial assessment; AI systems that can suggest medication-related problems during medication administration; and AI aids that can help them determine care priorities in the formulation of care plans. AI systems can be used to help nurses in identifying patients with more severe conditions, allocating nurse staffing resources, and improving nurse productivity. The successful implementation of systems is mainly based on the engagement of the nurses with the systems, and particularly with what they give as a result of the systems.
Ethical Issues
While technology can help, AI applications in clinical nursing raise unique ethical concerns that must be resolved. AI systems could also threaten nurses' autonomy by encouraging clinicians to rely on the AI system instead of making clinical decisions (Levin et al., 2025). Thus, it is likely that if the use of an AI system becomes the norm, it will lead to deskilling. However, the problem of accountability only further adds to questions. Who is at fault for the harm caused by the use of AI systems in healthcare? Is the AI system developed by the nurse, the institution, or the company? From an ethical perspective, this ‘accountability vacuum' is problematic within the nursing profession, where there are strict ethical codes in place. The role of nurses remains the same, and nurses need to maintain and demonstrate their clinical accountability when using AI systems or other related tools to support clinical practice. There is the potential for AI systems to become biased. Bias occurs when AI systems are trained on historical and unequal data, which in turn becomes a source of bias and inequality. AI systems trained with historical and inequitable data will be inequitable and biased, and often perform poorly with marginalized and low- resourced populations. Nurses need to be sensitive and to think critically about AI systems.
Generative AI on Patient Outcomes and Nurse Workload
There is preliminary evidence suggesting that generative and conversational AI may have a positive effect on certain patient outcomes, such as education, medication adherence, and post- discharge follow-up. Tools such as the Quincy chatbot help monitor patients after discharge and verify that follow-up appointments are scheduled, that medications are refilled, and that patients are reporting symptoms. This can aid the nursing staff in performing early interventions and may help reduce the risk of patients being readmitted (Brydges, 2025). AI-powered virtual assistants that offer electronic educational material can aid in the enhancement of patient understanding and can help improve engagement and adherence to treatment plans (Brydges, 2025). However, the evidence of large-scale, well-designed studies that can show a direct causal relationship between the use of generative AI and a decrease in patients’ morbidity and/or mortality is lacking because a majority of these studies are still in the development and/or testing phases (Cant et al., 2026).
In the case of nurse workload, the use of generative AI, together with ambient voice technologies, is intended to decrease the workload associated with documentation and streamline the performance of administrative tasks. Ambient voice technology can record conversations that occur at the bedside and then capture that data in an electronic health record. When this technology is integrated in the healthcare setting, it allows nurses to once again be able to provide direct patient care (Brydges, 2025). AI, combined with natural language processing to capture and extract clinical information from nursing documentation, can reduce the amount of time spent on data entry and improve workflows (Brydges, 2025). Even with these potential work applications, the evidence of effectiveness in the real world is lacking because of limited controlled studies on the work applications and the lack of practicing nurses on the AI design teams.
Conclusion AI is changing the future of clinical nursing and presents novel opportunities for decision support, workload, and patient safety management. The preparation, critical engagement, and quality of the nurse using AI are what are crucial to successful integration, rather than advanced algorithms. AI-based decision support will mean that nurses will experience new roles, such as interpreters of outputs, guardians of ethics, and custodians of justice through equitable care. The introduction of AI will not eliminate the nursing profession. The work of nurses is going to be more complex, complicated, and involved in the provision of care with the help of artificial intelligence.
