Clinical decision support systems (CDSS) are widely used to prevent adverse drug events (ADE) but can generate alerts with low clinical relevance resulting in alert fatigue and high override rates. This review summarizes existing research in the use of artificial intelligence (AI) to reduce alert fatigue in CDSS. Included studies reported AI decreased inappropriate alerts. However, none of the studies reported external validation or transparency of model development.