A PLS-SEM analysis of people, management, and organisational culture influences on AI-driven hospital facilities management systems

Abstract

Introduction: As hospitals increasingly integrate artificial intelligence (AI) into facility and asset management, understanding the organisational and human factors influencing this transition has become essential. Despite growing interest in AI-driven facility management, there is limited empirical evidence on how organisational culture, management commitment, and staff-related factors shape AI adoption in hospital environments. Methods: This study employed Partial Least Squares Structural Equation Modelling (PLS SEM) to analyse data from a diverse sample of built environment professionals with experience in hospital asset and facilities management. The model assessed the influence of organisational culture, managerial commitment and people-related factors on staff adaptability and AI integration. Results: The structural model demonstrated strong explanatory power (R2 = 0.901), confirming that organisational culture significantly influences both staff adaptability and AI integration within hospital facility management systems. Unexpectedly, hypotheses related to people factors (H1) and management commitment (H2) were not statistically significant. These results may be attributed to sample characteristics or potential measurement limitations. Discussion: The findings highlight the dominant and necessary role of organisational culture in shaping AI adoption within hospital facility management—overshadowing individual-level and managerial influences. This suggests that fostering a conducive organisational culture may be more critical than isolated managerial directives or individual competencies when implementing AI-driven systems. The study provides actionable insights for hospital administrators and policymakers aiming to align AI implementation strategies with organisational readiness, thereby contributing to the emerging body of knowledge on AI adoption in healthcare facilities management.