To assess and summarize the impact surgeon learning curve effects could have on surgical metrics, clinical outcomes, and cost-benefit decisions in robot-assisted surgery across all surgical procedures. A systematic literature search of MEDLINE, MEDLINE In-Process, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and NHS Economic Evaluation Database were searched from 2012 to February 5, 2018. There were 2,316 total publications identified with potentially relevant information. From the systematic search, 68 studies were included in this review (49 in surgical setting; 19 in simulator/training setting). Of the 49 surgical studies, 80% were retrospective, 73% were single-arm, and all were observational in design. The number of surgeons per study was small; 67% of studies included fewer than five. The most frequent specialties were urology (n=20), general surgery (n=13), and gynecology (n=7). Time-based variables were the most commonly reported to assess learning curves (86% of studies), and the most reported individual metric was operative time (67% of studies). Other measures, including length of hospital stay, morbidity/mortality rates, and specialty-specific metrics, were less commonly reported. Of the major surgical, safety, and recovery metrics captured within this review, operative time (67%), complication rate (18%), and length of stay (10%) were reported most frequently, respectively. When evaluating the evidence base, the variability in results between studies and surgeons makes it challenging to synthesize a reliable estimate for length and burden of the learning curve for any one procedure. The literature lacks studies with high-quality designs assessing surgeon learning curves in robot-assisted surgery. In addition, the methods used to assess learning curves are poorly described and frequently inadequate. Opportunities remain to establish quantitative, evidence-based approaches to measuring and defining learning curves in robotic surgery, as well as estimating the clinical and economic burdens associated with surgeon learning.