A glance into the future of artificial intelligence-enhanced scalable personalized training: A response to Kopelovich, Brian, et al. (2025) and Kopelovich, Slevin, et al. (2025).

The two articles by Kopelovich, Brian, et al. (2025) and Kopelovich, Slevin, et al. (2025) mark a new era in psychotherapy research and practice. The articles detail the development and validation of one of the first conversational artificial intelligence- (AI-) enhanced psychotherapy training tools, with profound implications for the future of clinical training. Following the new trail blazed by Kopelovich, Brian, et al. (2025) and Kopelovich, Slevin, et al. (2025), this commentary traces some of the most promising future directions for clinical training and research. In clinical training, trainees will be able to practice therapeutic skills and techniques with virtual clients before working with real ones. After mastering common therapeutic skills and treatment-specific techniques, they will begin treating real clients and receive detailed, immediate, and constructive AI-based feedback on their work to augment supervision sessions. Posttraining, clinicians can maintain and enhance their clinical expertise, acquire new skills, and incorporate the latest evidence-based knowledge into their practice through AI-based solutions. In research, it will be possible to explore the most effective techniques to be used by trainees and therapists at certain moments in a therapeutic session with individual patients, enabling the development of more precise and personalized therapeutic interventions. It will also be possible to explore the most effective trainee-specific supervision approaches to enhance a transformative experience and serve as a catalyst for the trainee's professional identity development within the supervisor-supervisee relationship, augmented by a systematic mapping of the trainee's strengths and areas for improvement. (PsycInfo Database Record (c) 2025 APA, all rights reserved).