JMIR Publications

ABSTRACT

Artificial intelligence (AI) is already in the consulting room, whether clinicians invite it or not. OpenAI reports more than 800 million regular users of ChatGPT and more than 40 million people turning to the platform daily for health questions, yet only 16% of large language model–based mental health tools have undergone clinical efficacy testing. Professional guidance and regulation remain fragmented. Clinicians are therefore practicing in a gap between a patient reality that cannot be ignored and a professional infrastructure not yet built. We argue that neither enthusiastic adoption nor principled abstention is sufficient in the current environment. The clinician who refuses to discuss clinically material patient AI use is not preventing that use; they may lose visibility into a factor materially affecting the therapeutic process. The clinician who adopts AI without structured evaluation exposes patients and practice to avoidable harm. The stance we propose is structured harm reduction within the therapeutic relationship: invite discussion at intake, integrate material use into case formulation, discuss benefits and limits, establish crisis boundaries, monitor across treatment, and address termination planning. Clinician-initiated use is a separate choice requiring evidence, consent when applicable, privacy safeguards, and accountability. We propose a phased clinical framework spanning pre-intake through termination, anchored by the GUIDE mnemonic—Gather, Understand, Inform, Document, Evaluate—as an operational wrapper for daily practice. GUIDE and the phased framework are conceptual, unvalidated proposals. We distinguish ethical recommendations, established legal duties, and predicted standards; scope the legal discussion to the United States; integrate equity and subgroup performance; and offer proportionate implementation. The patients who seek care in an AI-saturated world deserve professional infrastructure capable of holding innovation and patient protection in informed balance.