Abstract

Many adolescents who compulsively game, scroll, or gamble online never receive treatment. Therapy is expensive, clinicians are scarce and waitlisted, and stigma weighs differently on boys and girls and across cultures. This literature review defines behavioral addiction, documents its neurological and psychosocial effects on youth aged nine to eighteen, and asks whether artificial intelligence can close the treatment gap. The evidence reviewed suggests that natural language processing, machine learning, and conversational agents answer the barriers point by point: they cost little, are available at any hour, preserve anonymity, screen objectively, and can personalize engagement. The review weighs those advantages against data privacy risks, algorithmic bias inherited from unrepresentative training data, and the plain fact that a machine cannot feel empathy. The paper concludes that artificial intelligence works best as a supplement to human clinicians within a hybrid model of care.