Abstract

The global rise of substance-related and behavioral addictions highlights the need for scalable, accessible, and evidence-based psychological interventions. Traditional forms of counseling and rehabilitation often fail to ensure timely support, continuity of care, and sufficient therapist availability. This study aims to analyze and systematize international research on the integration of artificial intelligence (AI) chatbots into psychological support for addiction treatment.

Literature was searched in PubMed, Scopus, Web of Science, and Google Scholar (2017–2025) using predefined keywords; inclusion focused on chatbot interventions for substance-related or behavioral addictions reporting empirical outcomes or validated therapeutic frameworks. Six representative models were analyzed: Woebot/W-SUDs, Tess, Chatbot-Assisted Therapy (CAT) for methamphetamine use, Quin for smoking cessation, the simulation-based LLM system ChatThero, and a field-defining systematic review.

The analysis demonstrated that chatbot-based interventions are feasible and acceptable for individuals with substance-use and behavioral addictions. Reported outcomes include reduced craving intensity, improved emotional regulation, and increased engagement in treatment. CAT showed measurable clinical improvement through toxicology data and retention rates, while Quin and ChatThero demonstrated enhanced adaptation to motivational interviewing and relapse-prevention frameworks.

The findings indicate that AI-mediated conversational systems can effectively complement traditional therapy by providing continuous support and promoting self-management. Further research is needed to verify long-term clinical outcomes, ensure ethical oversight, and adapt interventions to diverse cultural and linguistic contexts.