AI brain tumor segmentation and brain extraction algorithms are an essential step in image processing, however they are mainly developed in adults. Here, we aimed to explore the usability of these algorithms in a heterogenous pediatric population. In 42 brain pediatric tumor MRI, we compared manual mask with mask generated by the algorithms. Results were excellent for brain extraction, moderate for segmentation of contrast-enhancing tumors, and weak for non-enhancing T2-signal abnormalities. Some improvements are necessary to adapt this algorithm to pediatric brain tumors. However, borrowing strength from adults might be a feasible approach for AI implementation in rare pediatric populations.