Augmenting or Replacing Clinical Judgment? A Cross-Sectional Study on Healthcare Professionals’ Perceptions of Artificial Intelligence in Clinical Decision-Making"

Background: The use of Artificial Intelligence (AI) in clinical decision-making represents a paradigm shift within medical practice that has a potential to enhance diagnostic accuracy and improve patient outcomes. There are, however, concerns over its impact on clinical autonomy and its potential to replace human judgment. This study explores the perceptions of medical professionals towards use of AI in clinical decision-making and its perceived role in complementing or replacing clinical judgment. Methods: This study adopted a cross-sectional survey involving 104 health practitioners working in various clinical environments in Pakistan. A validated survey questionnaire gathered data on the attitudes of health professionals toward embracing AI, trust in AI-aided clinical decision-making, and challenges in AI adoption. Descriptive and inferential statistics were used to examine the correlations between demographics, clinical experience, and exposure to AI. Results: Most participants regarded AI as an add-on to improving clinical decision-making, and 78% assured that AI improves and does not replace human judgment. 15% expressed that AI can replace clinical judgment, and 99% stressed that the ultimate clinical decision is best made by physicians. Physicians acknowledged that AI would improve accuracy of clinical diagnosis (77%) and personalized treatment (62%). Notwithstanding this, ethical implications, loss of trust between patients and physicians, and over-reliance on technology were some of the issues that were identified. The main obstacles highlighted were the lack of proper training (64%), high implementation costs (48%), and ethical issues (67%). Participants were cautiously optimistic and preferred AI as an adjunct, not replacement, for clinical expertise. Conclusions: Although healthcare practitioners acknowledge the potential of AI to enhance clinical outcomes, it is hindered by training, cost, ethical, and professional autonomy issues. The results highlight the need for specific AI education, ethical protection, and human-centered implementation strategies. Real-world clinical workflow deployments and long-term effects of AI on clinical roles, patient care, and professional identity must be evaluated in future research.Keywords: Artificial intelligence, clinical decision-making, healthcare practitioners, clinical autonomy, AI integration, medical ethics, digital health.