Introduction: Artificial intelligence–enabled mobile point-of-care tools have gained increasing attention for their potential to support evidence-based practice and clinical decision-making in nursing. PubMed GPT is a generative AI tool designed to synthesize biomedical literature through natural language queries. However, evidence regarding its usability, perceived value, and acceptance among medical-surgical nurses remains limited.

Methods: This paper presents a narrative literature review synthesizing current research on artificial intelligence in nursing, mobile point-of-care technologies, and technology acceptance constructs relevant to PubMed GPT. Databases and recent peer-reviewed studies were examined to identify themes related to ease of use, perceived usefulness, interface satisfaction, perceived value, and attitudes toward AI.

Results: The literature consistently identifies perceived ease of use, perceived usefulness, interface satisfaction, and perceived value as key determinants of nurses’ acceptance of AI technologies. When AI tools are intuitive, clinically relevant, and aligned with nursing workflows, nurses report greater trust, satisfaction, and intention to use. Persistent barriers include concerns regarding accuracy, ethical accountability, data privacy, and professional autonomy. Notably, empirical studies focusing specifically on medical-surgical nurses’ real-world experiences with PubMed GPT are scarce.

Discussion: AI-enabled mobile point-of-care tools such as PubMed GPT show substantial promise for supporting evidence-based nursing practice. Addressing usability, trust, and ethical considerations while reinforcing professional judgment is essential for sustainable integration.