Understanding human-AI interaction in healthcare: the mediating role of trust and moderating influence of cognitive load

The integration of Artificial Intelligence (AI) in healthcare is often hindered by a lack of trust among healthcare professionals, impacting the effectiveness of Human-AI interaction. This study examines how Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) influence trust in AI, with trust mediating the relationship between these constructs and Human-AI interaction in healthcare settings. Additionally, the researcher investigates the moderating role of Cognitive Load, positing that higher cognitive demands may weaken the positive effects of trust on Human-AI interaction. By surveying doctors, nurses, and medical technicians in Malaysia, the study aims to provide a comprehensive understanding of these dynamics. It is expected to find that increased PU and PEOU enhance trust, leading to improved Human-AI interaction, while Cognitive Load may diminish the strength of this relationship. Anticipated findings will underscore the importance of designing AI systems that are intuitive, beneficial, and mindful of cognitive demands to optimise healthcare outcomes and clinician support. This research holds significant commercialisation potential as healthcare organisations increasingly seek AI solutions that enhance trust and facilitate effective collaboration between humans and AI.