A National Cross-Sectional Survey of Artificial Intelligence Patient Safety Reporting Infrastructure Available to US Nurses

BACKGROUND: Federal artificial intelligence (AI) safety governance depends on clinicians reporting AI-related patient safety concerns, yet national availability of nurse-facing reporting channels and related practice guidance is unknown. PURPOSE: To characterize formal AI safety reporting channels available to practicing US nurses and correlates of reporting. METHODS: A national cross-sectional survey of 1189 practicing US nurses was conducted in June to July 2026. RESULTS: Among 424 nurses who encountered an AI-related patient safety concern, 83 (19.6%) reported no formal channel for reporting it. Non-hospital nurses had higher odds of no channel than hospital-based nurses (odds ratio, 2.54; 95% confidence interval, 1.54-4.19). Where a channel existed, perceived severity predicted reporting (adjusted odds ratio, 2.47; 95% confidence interval, 1.77-3.45). CONCLUSIONS: One in 5 nurses with an AI-related patient safety concern lacked reporting infrastructure. Federal AI safety governance presupposes infrastructure that remains uneven across US care settings.