Mental health disorders are some of the greatest contributors to the global disease burden, and healthcare systems are struggling to provide scalable care of high quality. Artificial intelligence (AI)-based tools and applications are some of the most significant technological advances in the mental healthcare field. Researchers have spent decades to build, evaluate, and refine AI models to conduct tasks such as identifying the treatment intervention and rating the quality of treatment. These models have been utilized to monitor treatment quality, enhance training, support clinical documentation, and supplement client treatment support. However, significant limitations include the potential for algorithmic biases and ethical concerns regarding patient data privacy. While AI shows promise in addressing the mental health workforce shortage and improving the quality of care, successful implementation requires thoughtful integration. This review examines research in which AI as a complement to, not replacement for, human providers in mental health treatment.