Artificial Intelligence and Psychiatric Training: Opportunities, Challenges, and the Future of Mental Health...

Artificial intelligence (AI) is rapidly transforming healthcare delivery, research, and medical education. Within psychiatry, advances in machine learning, natural language processing, large language models (LLMs), and AI-enabled simulation are reshaping clinical practice and trainee education. Educational and clinical applications include personalized learning, virtual patient encounters, clinical decision support, longitudinal electronic health record (EHR) synthesis, automated feedback, and documentation assistance. These tools may strengthen diagnostic reasoning, psychopharmacology education, psychotherapy training, and administrative efficiency while allowing more time for patient-facing care. However, algorithmic bias, misinformation, privacy, academic integrity, cost, and overreliance may undermine independent clinical judgment. These risks are especially important for novice learners and in child and adolescent assessment, where chronological age does not capture cognitive development, cultural context, or nonverbal and affective cues. Empirical outcome data evaluating formal AI curriculum implementation in psychiatry residency and fellowship programs remain limited, with few studies assessing effects on trainee competence, clinical reasoning, error recognition, patient safety, or sustained clinical performance. This narrative review examines current applications, limitations, and ethical considerations and proposes a staged, competency-based curriculum in which trainees establish core interviewing, observation, and diagnostic skills before progressing to supervised clinical AI use. AI should augment, rather than replace, human interpretation, therapeutic relationships, and professional accountability. Accordingly, this review is primarily directed toward graduate medical education leaders, psychiatry residency and fellowship program directors, and clinical educators who are responsible for the development, implementation, and oversight of competency-based AI curricula within psychiatric training programs.