Purpose Artificial intelligence (AI) is an emerging technology in colonoscopy to improve adenoma (ADR) and polyp detection rates (PDR), with increasing evidence of its efficacy and cost-effectiveness. Current literature has focused on outcomes in expert endoscopists and is it unknown whether these benefits translate into a trainee population. This systematic review considers the effects of AI on trainee endoscopists in improving their ADR. Methodology MEDLINE, EMBASE and CENTRAL databases were searched in accordance with PRISMA guidelines for studies analysing the effect of trainee use of AI assisted colonoscopy on ADR and/or PDR. The primary outcome was ADR. Secondary outcomes included PDR, adenoma miss rate (AMR), polyp miss rate (PMR), lesion characteristics and withdrawal time. Results 4 studies were included, which had heterogenicity in outcomes, comparison groups and inclusion criteria. Initial analysis demonstrated an increase in ADR and PDR in trainees with AI to levels comparable to experts. However, there were no significant differences in ADR and PDR in trainees with AI vs trainees without AI, despite having a significant improvement in AMR in the same study. AI did not change the polyp clinicopathology found, though there was conflicting evidence about which lesions trainees missed in the majority. AI did not increase the withdrawal time. Conclusion This review supports AI as a viable aid for trainees to ensure the quality of their colonoscopies is similar to expert endoscopists. However, there is a lack of evidence demonstrating improvement comparing trainees with AI vs trainees without AI and no evidence analysing the long-term effects of AI on trainee competency.