Pediatric nursing in the AI era: from clinical integration to ethical practice to education

Artificial intelligence (AI) is rapidly emerging as a foundational technology, reorganizing the entire medical field and extending far beyond simple technological innovation. This transformation is occurring across various domains of medicine. However, pediatrics, which represents a small proportion of healthcare resources compared to other population groups [1], presents especially complex ethical and practical challenges. As AI systems become increasingly embedded in areas such as clinical decision support, diagnosis, disease prediction, and personalized treatment, pediatric nursing must play a central role in integrating these new technologies into practice and reflecting on their ethical implications. In this editorial, we examine the expanding role of AI in pediatric nursing practice, its anticipated benefits, and critical considerations that must not be overlooked, drawing on recent research findings and ongoing ethical discussions.

1. AI-Based Clinical Decision Support System (AI-SDSS) and the Role of Pediatric Nurses

Clinical decision support systems (CDSS) based on machine learning have the potential to improve early disease detection and identify risk groups in pediatric care. Notably, AI-CDSS have demonstrated promising performance, achieving high specificity and low false-positive rates compared to conventional rule-based models in diagnosing severe pediatric diseases such as sepsis, traumatic brain injury, and pneumonia [2]. These systems can provide real-time alerts in clinical settings, recommend evidence-based interventions, and help reduce the cognitive burden on healthcare providers. For example, a randomized controlled study showed that pediatric asthma management using AI-CDSS led to improved efficiency in clinic time and cost savings, without adversely affecting clinical outcomes [3].

However, the value of these systems extends beyond simple performance metrics. To provide meaningful clinical support, models must be interpretable and seamlessly integrate into clinical workflows, ultimately aligning with clinicians’ professional judgment. Pediatric nurses serve in multiple roles as emergency responders, care coordinators, and family communicators. They are uniquely positioned to accurately interpret and apply recommendations from AI systems in clinical practice. Therefore, understanding and using AI (i.e., AI literacy) should be considered an essential component of future pediatric nursing competencies.

2. Redefining the Practical Role of Pediatric Nurses in the AI-Driven Digital Health Age

Traditionally, pediatric medicine has focused on diagnosing and treating acute illnesses. However, the field has shifted toward an integrated model that emphasizes the holistic health and well-being of children. AI is now recognized as a key driver accelerating this change. Indrio et al. [4] introduced the integration of AI into the “7P model” of pediatric medicine. This model emphasizes a prediction-centered approach, strengthens family engagement, and promotes multidisciplinary collaboration to address complex health needs through a personalized, predictive, preventive, participatory, precise, and multi-professional framework.

AI enables early prediction of diseases such as autism spectrum disorder, neonatal sepsis, and childhood obesity by analyzing diverse data sources, including genetic information, developmental assessments, and social determinants of health. Pediatric nurses can serve as key mediators who interpret predictive data, implement preventive interventions tailored to the child and family’s circumstances, and coordinate care that is culturally responsive.

In particular, the rise of AI-integrated digital health technologies, such as wearable devices, presents significant opportunities at the intersection of nursing and AI. For children with chronic conditions like asthma or type 1 diabetes, AI-powered wearables can monitor their health in real time at home. Nurses play a crucial role in teaching families how to use these devices, recognizing warning signs, and managing virtual follow-ups. Additionally, in areas with limited healthcare resources or restricted access due to geography, AI-based telehealth technologies can help improve the continuity and equity of pediatric care.

3. Ethical Applications of AI in Pediatric Nursing and the Role of Nurses

Despite significant technological progress, the widespread adoption of AI in pediatric care depends on building caregivers’ trust and meeting ethical obligations. Berghea et al. [5] conducted a cross-sectional study among Romanian parents to evaluate attitudes toward the use of AI in their children’s healthcare. While overall acceptance was high, substantial differences emerged based on educational level. Caregivers with lower educational attainment were more likely to resist AI-based decision-making, primarily due to concerns about technological errors and a perceived disconnect from medical staff. Nearly 89% of all respondents indicated that human supervision was necessary, and over 90% required prior consent and clear explanations before AI implementation. These findings underscore a fundamental ethical tension in pediatric care: balancing the efficiency of technology, trust rooted in human relationships, and respect for caregivers’ autonomy. Unlike adults, children cannot make fully informed decisions, and caregivers may lack professional understanding of the limitations or reasoning behind AI systems. Therefore, pediatric nurses should play a key role in providing transparent information, fostering shared decision-making, and ensuring robust ethical safeguards with caregivers when integrating AI into treatment plans.

Additionally, the impact of AI on equity and justice in healthcare should not be overlooked. Several studies have raised concerns that algorithmic bias may worsen existing health disparities. For example, some urinary tract infection prediction models have underestimated disease prevalence in Black children, and differences in the sensitivity of sepsis diagnosis across racial groups have been reported [2]. Nursing leadership should critically assess the cultural appropriateness and fairness of AI tools, and actively promote the collection and use of complete and representative data to ensure their effectiveness.

4. Nursing Education in the AI Era: Integrating Practical Competence and Ethical Sensitivity

Research on AI is expanding rapidly, yet there remain few examples of its integration into real-world pediatric nursing interventions. Many AI models are developed in academic or resource-rich environments, which can limit their effectiveness when applied to diverse populations or varied clinical settings. The absence of standardized data systems, clinician skepticism, and insufficient systematic education on AI capabilities further widen the gap between development and practical application. Pediatric nurses are therefore required to adopt a dual role: not only as early adopters of AI technology but also as advocates for child-centered ethical innovation.

As key mediators who bridge AI analysis with the health needs of children and families, nurses are crucial in translating complex predictive information into actionable healthcare plans. They can also enhance the real-world relevance of AI by providing feedback to developers about usability, intuitiveness, and the integration of these tools into clinical workflows. In this regard, nurses must not only act as end users of technology but also as co-designers of AI solutions within interdisciplinary collaborative teams.

To carry out these roles effectively, digital health and AI-related competencies should be incorporated into pediatric nursing curricula. This education must go beyond basic technical proficiency to include the critical evaluation of AI-based tools, ethical judgment and accountability, and effective communication strategies with guardians and children about responsible technology use. Just as infection control became a core component of nursing education after the COVID-19 (coronavirus disease 2019) pandemic, understanding and applying algorithms should now be established as a central focus in nursing education for the AI era.

5. From Support to Collaboration: AI’s Role as a Companion in Human-Centered Nursing

As pediatric care undergoes a transformative shift, it is more important than ever to regard AI not merely as a technical tool but as a strategic partner in providing human-centered, evidence-based care. AI holds significant potential to augment nurses’ vigilance, enable personalized care, and enhance care coordination. However, this potential can only be fully realized when AI is used thoughtfully and ethically, grounded in the principles of transparency, accountability, and empathy.

Today, pediatric nursing stands at a critical crossroads. The integration of AI should not replace the core values of relationship-centered nursing but should instead expand its scope and depth through predictive insights, preventive strategies, and personalized support. As nurses have long safeguarded the dignity and well-being of their patients, the profession must now take the lead in guiding the use of AI technologies—ensuring they serve the best interests of children and families.