Developing an AI Literacy Curriculum for Graduate Mental Health Training: A Mixed-Methods Needs Assessment Study

Artificial intelligence (AI) is increasingly influencing mental health practice, yet graduate training programs provide limited structured preparation for its ethical and clinical use. This exploratory mixed-methods needs assessment examined Marriage and Family Therapy (MFT) graduate students’ experiences, perceptions, and educational needs related to AI. Survey data from 33 students included quantitative items assessing AI exposure, self-reported confidence, attitudes, ethical concerns, and training priorities, alongside open-ended responses analyzed thematically. Findings indicated that students frequently used AI, primarily for academic purposes, but reported lower confidence in understanding AI systems, evaluating AI-generated information, and applying ethical decision-making principles. Qualitative findings highlighted tensions between AI’s perceived benefits and concerns about overreliance, ethical risks, and preserving human connection in therapy. Integration of findings informed a preliminary AI literacy curriculum emphasizing foundational knowledge, clinical applications, and ethical, systemic, and relational evaluation. Findings support intentional AI literacy education to prepare emerging clinicians for responsible engagement with evolving technologies.