Artificial intelligence (AI) is rapidly transforming the healthcare landscape, presenting significant opportunities and complex challenges for clinical practice (Li et al., 2025). This ongoing transformation aligns with the broader framework of “Healthcare 4.0,” which emphasizes the integration of advanced technologies, including AI, big data analytics and the Internet of Things, to enhance the efficiency, personalization and quality of care delivery (Stoumpos et al., 2023). AI applications are increasingly being used in clinical decision support systems, diagnostic processes, patient monitoring and individualized treatment planning, which can potentially optimize healthcare outcomes and resource use (Sarıkahya et al., 2025, Wei et al., 2025, Bozkurt et al., 2025). Within this evolving technological paradigm, nursing, positioned at the core of patient care, plays a pivotal role. As frontline caregivers and care coordinators, nurses are uniquely situated to leverage AI tools to enhance clinical decision-making, streamline workflows and improve patient safety and satisfaction (Jiang et al., 2017). However, this integration also demands acquiring new competencies, particularly in AI literacy, ethical evaluation and interdisciplinary collaboration (Sumengen et al., 2025). Ensuring that nurses are equipped with the necessary knowledge and skills is essential for the successful and ethical implementation of AI in healthcare practice.

As AI tools become increasingly integrated into healthcare environments, nurses must be adequately prepared to work alongside these technologies (Labrague et al., 2023, Watson et al., 2020). This integration necessitates systemic digital transformation and the development of digital competencies and adaptive mindsets among healthcare professionals. Nurse educators are critical in preparing students for technology-integrated care, ensuring that future nurses can engage effectively with AI-supported systems (Kaya et al., 2025). Within this framework, AI literacy, the knowledge, skills and attitudes needed to understand, evaluate and interact with AI, has emerged as a vital competency in nursing education (El-Sayed et al., 2025). Enhancing AI literacy among nursing students contributes to their professional growth, innovation and the safe integration of AI into clinical practice. AI-literate nurses are expected to interpret AI-generated outputs, monitor AI-assisted devices and uphold ethical, patient-centered care in collaboration with these technologies. Nursing curricula must incorporate AI-related content and informatics training to meet these evolving demands and build conceptual understanding and practical skills (Castonguay et al., 2023). Without adequate preparation, nurses may struggle to effectively use AI tools, ultimately limiting their potential to improve patient outcomes and optimize healthcare delivery (Buchanan et al., 2020, von Gerich et al., 2022). Therefore, equipping nursing students with the competencies required for AI-enhanced healthcare is timely and an essential educational imperative.

AI literacy and attitudes toward AI have emerged as critical areas of inquiry in contemporary nursing education research (Özçevik Subaşi et al., 2025). AI literacy equips nursing students with the ability to critically assess AI-driven applications, such as clinical decision support systems, risk prediction algorithms, or treatment recommendations (Sumengen et al., 2025). In parallel, students' attitudes toward AI, whether they perceive it as a supportive tool or a potential threat, play a significant role in adopting and integrating such technologies into clinical practice ((Labrague et al., 2023; Derakhshanian et al., 2024). While positive attitudes can facilitate engagement and learning, negative perceptions may create resistance and impede effective use. Recent empirical studies indicate that nursing students generally exhibit moderately positive attitudes toward AI (Cho and Seo, 2024, Kwak et al., 2022, Taskiran, 2023). For instance, a recent meta-analysis reported that 65 % of healthcare students expressed favorable views toward AI, although their knowledge levels remained moderate (Amiri et al., 2024). This discrepancy between attitudinal optimism and cognitive understanding underscores a significant educational gap that must be addressed through targeted curriculum design. Emerging evidence further suggests a strong correlation between AI literacy and attitudes, with higher levels of literacy associated with more favorable perceptions of AI (Sumengen et al., 2025). These findings highlight the necessity of integrating comprehensive AI education into nursing curricula to foster competence and confidence in future healthcare professionals.

In Türkiye, research has shown that while nursing students hold positive attitudes toward AI, their self-reported literacy remains moderate (Sumengen et al., 2025). However, few studies have examined the relationship between AI readiness, literacy and attitudes. Most studies explore these elements separately. For example, Yalçınkaya et al. (2024) reported a correlation between attitudes and readiness but noted a lack of integrated studies. This points to a significant research gap. AI readiness a student’s preparedness to engage with AI likely depends on both what they know and how they feel about AI. Improving literacy may build confidence, while positive attitudes may enhance learning motivation. Therefore, this study aims to examine the relationships between nursing students’ readiness for medical AI, their AI literacy and their attitudes toward AI.