Abstract
Artificial intelligence (AI) has emerged as a transformative technology in healthcare, offering significant opportunities to enhance clinical decision-making, improve patient safety, and optimize healthcare service delivery. Despite the increasing adoption of AI-supported clinical decision support systems worldwide, empirical evidence regarding their impact on nursing performance in developing healthcare systems remains limited, particularly in Pakistan. This study investigated the influence of AI-supported clinical decision-making on nursing performance in Pakistani hospitals by examining the mediating role of clinical decision quality and the moderating role of digital health readiness. Grounded in Task–Technology Fit (TTF) Theory, the study adopted a quantitative, cross-sectional, explanatory research design. Primary data were collected from registered nurses employed in public and private hospitals across Pakistan using a structured questionnaire. The proposed conceptual framework was empirically tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that AI-supported clinical decision-making significantly improves clinical decision quality and nursing performance. Clinical decision quality was found to partially mediate the relationship between AI-supported clinical decision-making and nursing performance, demonstrating that improved decision accuracy and evidence-based clinical judgments serve as important mechanisms through which AI enhances nursing effectiveness. Furthermore, digital health readiness significantly strengthened the positive relationship between AI-supported clinical decision-making and clinical decision quality, highlighting the importance of organizational digital infrastructure and technological preparedness in maximizing AI benefits. The study extends Task–Technology Fit Theory by integrating clinical decision quality and digital health readiness into a comprehensive framework explaining AI-enabled nursing performance. The findings provide important theoretical, managerial, and policy implications for healthcare administrators, nursing leaders, and policymakers seeking to accelerate digital health transformation, strengthen AI adoption, improve nursing performance, and enhance the quality and safety of healthcare services in Pakistan