JMIR Publications

ABSTRACT

Background:

Artificial intelligence (AI) is increasingly being integrated into healthcare delivery, creating new demands for nurses’ digital competencies. Existing AI-related nursing education has primarily focused on developing learners’ AI literacy and their ability to understand and utilize AI technologies, particularly among nursing students and newly graduated nurses. However, in-service nurses, who possess extensive clinical experience and first-hand knowledge of frontline care challenges, have received limited attention as active contributors to the design and development of AI-based solutions. Engaging nurses in transforming clinical problems into AI-supported tools may provide a valuable pathway to enhance AI competency in nursing practice and promote their transition from AI users to AI co-creators.

Objective:

This study aimed to design and evaluate an ADDIE-model-driven AI training workshop centered on clinical intelligent agent development for in-service nurses, and to comprehensively examine its effects using an explanatory sequential mixed-methods design.

Methods:

An explanatory sequential mixed-methods design guided by the ADDIE instructional framework was adopted. A convenience sample of 28 registered nurses with at least two years of clinical experience from a tertiary cardiovascular hospital participated in an AI co-creation-oriented learning program combining theoretical instruction with clinical AI agent development activities. Nurses’ AI competency and information competence were assessed before and after the program, whereas self-directed learning ability and course satisfaction were evaluated after completion. Following quantitative assessment, semi-structured interviews were conducted with 13 purposively selected participants to explore their experiences, perceived value, and challenges during AI agent co-creation.

Results:

After completing the AI theoretical training and engaging in clinical AI agent design and development activities, nurses demonstrated significant improvements in overall AI competency, information competence, and self-directed learning ability (all P< 0.05). During the program, participants collaboratively developed 19 AI agent prototypes addressing authentic nursing challenges identified from clinical practice, illustrating their capacity to transform frontline care needs into AI-supported solutions. Qualitative analysis revealed three major themes: (a) the multidimensional educational and clinical value of AI agent development, including improvements in clinical workflow optimization, nursing education, and research engagement; (b) challenges encountered during AI agent development and implementation, including technical limitations, clinical safety concerns, and teamwork barriers; and (c) recommendations for optimizing future AI learning programs.

Conclusions:

An AI agent-based learning program integrating theoretical instruction with clinical problem-driven development activities may enhance in-service nurses’ AI competency, information competence, and self-directed learning ability. Beyond improving AI literacy, this approach enables nurses to actively participate in transforming frontline clinical challenges into AI-supported solutions, highlighting their potential role as co-creators in AI-enabled healthcare innovation. Although the single-center design, small sample size, and lack of long-term follow-up limit generalizability, these findings provide preliminary support for incorporating AI co-creation-oriented learning approaches into nursing continuing education. Future multicenter longitudinal studies are warranted to further evaluate the sustainability and clinical impact of nurse-involved AI solution development. Clinical Trial: none