Nursing leadership and performance metrics in artificial intelligence integrated gastrointestinal surgical care: A narrative review

Table 4 Implementation risks and nursing leadership safeguards in artificial intelligence-supported surgical pathways

Implementation risk	How it may appear in practice	Potential consequence	Nursing leadership safeguard
Alert fatigue	Frequent low-priority alerts during already busy ward shifts	Important signals may be ignored or delayed	Define alert priority levels; monitor alert volume; remove non-actionable alerts; collect staff feedback
Unclear accountability	Alert visible to several professionals, but no one is clearly responsible for first response	Delay in reassessment or escalation	Assign first-response responsibility; define response time; document ownership of action
Over-reliance on AI	Staff wait for digital confirmation before escalating bedside concern	Clinical deterioration may be underestimated when no alert is generated	Reinforce that nursing concern overrides absence of alert; include this principle in training
Under-use of AI	Alerts are ignored because they are poorly understood or not integrated into workflow	Technology has little real-world clinical effect	Provide scenario-based training; integrate alerts into handover and ward routines
Poor interpretability	Nurses receive a risk score without explanation of relevant contributing factors	Low trust, inconsistent response, or inappropriate escalation	Require clinically understandable alert displays; include contributing variables where possible
Documentation burden	AI adds new forms or fields without reducing existing duplication	Increased workload and incomplete records	Align documentation templates with nursing workflow; remove duplicate fields; audit documentation quality
Inequitable performance	Model performs less well in frail, older, complex, or underrepresented patient groups	Risk may be underestimated or overestimated in vulnerable patients	Monitor subgroup performance; encourage clinical override; review unexpected deterioration events
Weak handover integration	Risk information remains in the electronic record but is not communicated during transitions	Receiving nurses may not know what to monitor	Add AI-derived risk status to structured perioperative handover
Lack of staff confidence	Nurses are unsure whether they are expected to trust, question, or act on alerts	Variable adoption and inconsistent practice	Use case-based education, simulation, and feedback after real alerts
Unmeasured implementation	Institution installs AI tool but does not evaluate nursing workflow or patient safety impact	No evidence that care delivery improved	Use a nursing-sensitive audit dashboard before and after implementation

AI: Artificial intelligence.