A scoping review of artificial intelligence-enabled wearables for medication adherence

Abstract Medication non-adherence remains a major global public health challenge with substantial clinical and economic burden. Artificial intelligence (AI)-enabled wearables may offer new opportunities to support medication adherence management. This scoping review assesses the current evidence on AI-enabled wearables for medication adherence, focusing on their applications, performance, and clinical translation. We screened three databases for literature published up to September 18, 2025. A total of 6102 records were identified, and 17 studies met the inclusion criteria. Current applications were concentrated on medication-taking behavior and ingestion event recognition, with fewer studies addressing longitudinal medication adherence assessment or non-adherence risk prediction. No included study evaluated AI-enabled wearables for personalized intervention. Most studies focused on technology development and internal validation. Although reported performance was generally favorable in controlled settings, evidence remains limited for external validation, real-world effectiveness, clinical outcomes, and integration into routine care. These findings suggest that AI-enabled wearables are technically feasible for medication adherence monitoring, but their clinical value remains insufficiently established. Future research should move beyond recognition toward prospective risk prediction, personalized intervention, and clinically integrated decision support.