Challenges to The Adoption of Artificial Intelligence in Nursing Clinical Practice: A Cross- Sectional Study
Abstract:
Background: The integration of artificial intelligence into nursing clinical practice is increasing globally. However, several challenges may hinder its adoption. This study aimed to examine the challenges graduate nursing students anticipate facing when adopting artificial intelligence in clinical practice.
Methods: A descriptive cross-sectional study was conducted at the Graduate College of Al-Neelain Universi ty, Sudan. A total of 101 graduate nursing students were engaged using a systematic sampling method. Data was collected through a structured, self-administered questionnaire.
Results: The majority of participants (70.2%) did not receive formal training. Patient data privacy was iden tified as the most significant ethical concern (82.2%), followed by accountability for errors (50.5%).
Conclusion: Significant challenges remain in the adoption of artificial intelligence in nursing practice, par ticularly inadequate training, accountability in errors, and ethical concerns related to privacy and account ability. Strengthening artificial intelligence education and regulatory policies is essential for responsible integration.
