This systematic review hosted by Rabie Adel El Arab & Omayma Abdulaziz Al Moosa uses comparative economic models to analyze a total of 19 economic evaluations published between 2010 and 2023. These economic evaluations mainly stem from clinical AI interventions in fields across oncology, cardiology, and ophthalmology. Subsequent methods of the study were characterized by appraising reporting quality using the CHEERS 2022 checklist and Drummond’s criteria to assess both trial-based and model-based studies. Arab and Moosa also found that AI applications have enhanced quality-adjusted life years (QALYs) and have consequently achieved incremental cost-effectiveness ratios (ICERs) that are well below conventional thresholds at both the patient and system levels. However, despite these encouraging findings, Arab and Moosa note that many of the studies relied on static modeling approaches which may have overestimated the long-term benefits. Specifically, the reports rarely included indirect and infrastructural costs, all whilst providing limited attention to subgroup and equity analyses. Overall, the article displayed high levels of reporting quality but still emphasized the need for broader considerations of population density and comprehensive modeling.