The SMART Framework: A Hierarchical Model for Moving Generative AI in Psychotherapy from Capability to Clinical Utility (Preprint)

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Abstract
UNSTRUCTURED Generative artificial intelligence (GenAI) is rapidly entering psychotherapy, from clinician training and decision support to patient-facing tools and direct involvement in therapeutic sessions. Yet much of the discussion remains focused on what these systems can do, rather than on where and for what purpose their capabilities can be translated into meaningful clinical use. This reflects the broader capability-to-utility gap between demonstrated technological performance and clearly defined value in care. We propose the SMART framework to organize GenAI applications across five levels of increasing integration into psychotherapy: Skill building, where GenAI supports clinical training without patient contact; Mentoring, where it supports clinician judgment around real cases; Assisting, where it interacts directly with patients between sessions as an adjunct to therapist-led care; Reflecting, where it observes and analyzes the therapeutic session without intervening; and Transforming, where it actively participates within the session under clinician leadership. Across these levels, increasing proximity to the patient and deeper integration into the therapeutic encounter are accompanied by changing clinical, ethical, evidentiary, and oversight requirements. By linking GenAI applications to their specific place and purpose in care, SMART provides a shared language for clinicians, researchers, developers, and policymakers. It offers a basis for more proportionate evaluation and regulation and for a research agenda focused on when GenAI capabilities translate into safe, clinically useful, and accountable psychotherapy.

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