By: Robert Hinyub, III

Written by: Kirti Vaidya Reddy, Quarles and Robert Hinyub III, Breazeale, Sachse & Wilson, L.L.P.

As some studies estimate that nearly 23% of the adult population lives with a mental illness, the integration of artificial intelligence (AI) into mental health care has transformative potential in terms of accessibility, cost reduction, personalization, and provider efficiency. To improve the prediction of risk of mental health disorders and the treatment of mental health, AI is commonly used for: (1) AI therapy, (2) wearables that interpret bodily signals using sensors and providing assistance when needed, (3) diagnosing and predicting outcomes by analyzing patient data, (4) improving adherence to treatment by using AI to predict when a patient is likely to slip into noncompliance or issue reminders for medication or provider appointments, and (5) personalizing treatments and adjusting individual treatment plans. To support these advancements, the American Medical Association Current Procedural Terminology (CPT) Editorial Board has incorporated billing codes applicable to the use of AI as well as AI taxonomy that provides guidance for classifying various AI-powered medical services applications. While AI has potential to improve behavioral health care, it also presents challenges as technology is advancing at a much faster pace than regulatory controls that ensure safety and efficacy. This article discusses various challenges with the use of AI in the behavioral health setting and regulatory developments that are attempting to provide safeguards in this dynamic space.