Abstract Background Robotic-assisted minimally invasive surgery has improved patient outcomes and experiences in various surgical disciplines, demonstrating reduced complications, postoperative pain, and length of hospital stays. Within the field of bariatric surgery, the integration of robotic systems aims to further enhance patient outcomes compared to traditional laparoscopic procedures. However, the precise learning curve (LC) for robotic bariatric surgery has yet to be clearly defined. Considering this knowledge gap, our review aims to compile and analyse the most up-to-date evidence on LC outcomes in bariatric surgery procedures. Methods In this review, we searched PubMed, Embase, and Cochrane Central Library databases up to April 2023 to identify studies reporting LC outcomes for robotic bariatric procedures. The primary outcome was the number of operations required to reach LC stabilization. Secondary outcomes included surgeon characteristics, including the number of training surgeons, their prior laparoscopic and/or robotic experience, exposure to simulated robotic training and outcome measures, including complication rates, surgery duration, and length of stay. Our study is registered on PROSPERO (CRD42023425878), and no specific grants were received from funding agencies. Results Of 432 initial results, 18 articles were included. All were observational studies reporting 27 cohorts from 2006 to 2022, involving 2084 patients. There were one to four included surgeons. The overall median number of cases to overcome the LC was 35 (IQR 15-64). For gastric bypass (RGB), the median LC was 25 (IQR 15-69), while for sleeve gastrectomy (RSG), it was 31 (IQR 20-86). The overall operation time was 185 minutes (IQR 124-197), with RGB at 152 minutes (IQR 139-196) and RSG at 98 minutes (IQR 85-110). Five studies used the CUSUM methodology, while others lacked specified LC determination approaches. Conclusions Our review highlights that the learning curve for bariatric surgery can be navigated relatively quickly and safely. However, it also reveals that the existing evidence on learning curves for robotic bariatric surgery is derived from a limited number of surgeons with unclear levels of prior surgical experience. Furthermore, the heterogeneity in evaluating learning curves poses challenges for comprehensive analysis. Future studies should aim to outline differences in outcomes between established laparoscopic methods and robotic bariatric procedures, providing further clarity in this field.