Artificial Intelligence–Supported Collaboration Between Nursing Technicians, Ems Technicians, Laboratory Technicians, And Dental Assistants In Saudi Hospitals: Pathways Toward Smart Patient Care Systems

Abstract

The integration of artificial intelligence into healthcare systems represents a transformative shift in how clinical technicians collaborate to deliver patient care. This review examines the current state and future potential of AI-supported collaboration among nursing technicians, emergency medical services technicians, laboratory technicians, and dental assistants within Saudi Arabian hospital settings. Through systematic analysis of peer-reviewed literature published between 2018 and 2025, this study identifies key mechanisms through which AI facilitates interprofessional communication, diagnostic accuracy, workflow optimization, and clinical decision support. Findings indicate that AI-enabled platforms significantly enhance real-time data sharing, reduce diagnostic delays, and improve patient outcomes across multiple clinical domains. However, implementation barriers including technological infrastructure limitations, workforce training gaps, and cultural adaptation challenges remain substantial. The Saudi Vision 2030 framework provides strategic impetus for digital health transformation, yet successful deployment requires addressing technical competency development, interoperability standards, and professional role evolution. This review synthesizes evidence on AI applications in clinical technician workflows, evaluates implementation frameworks specific to the Saudi healthcare context, and proposes a roadmap for developing integrated smart patient care systems that leverage AI to strengthen collaborative practice among allied health professionals.