To evaluate the impact of Artificial Intelligence Assisted Prevention and Management for Delirium (AI-AntiDelirium) on improving adherence to delirium guidelines among nurses in the intensive care unit (ICU).Between November 2022 and June 2023, A cluster randomized controlled trial was undertaken.A total of 38 nurses were enrolled in the interventional arm, whereas 42 nurses were recruited for the control arm in six ICUs across two hospitals in Beijing, comparing nurses' adherence and cognitive load in units that use AI-AntiDelirium or the control group.The AI-AntiDelirium tailored delirium preventive or treated interventions to address patients' specific risk factors. The adherence rate of delirium interventions was the primary endpoint. The other endpoints were adherence to risk factors assessment, ICU delirium assessment, and nurses' cognitive load. The repeated measures analysis of variance was utilized to explore the influence of time, group, and time × group interaction on the repeated measurement variable (e.g., adherence, cognitive load).A cumulative total of 1040 nurse days were analyzed for this study. The adherence to delirium intervention of nurses in AI-AntiDelirium groups was higher than control units (75 % vs. 58 %, P < 0.01). When compared to control groups, AI-AntiDelirium was found to be significantly effective in both decreasing extraneous cognitive load (P < 0.01) and improving germane cognitive load (P < 0.01).This study supports the effectiveness of AI-AntiDelirium in enhancing nurses' adherence to evidence-based, individualized delirium intervention and also reducing extraneous cognitive load.A nurse-led systemshould be applied by nursing administrators to improve compliance with nursing interventions among ICU nurses.Copyright © 2024 Elsevier Ltd. All rights reserved.