The global rise in psychoactive substance use and non-substance-related addictive disorders presents a significant public health challenge. While a number of interventions have been developed to prevent and treat these problems, there is an ongoing effort to develop new effective options. These initiatives are especially important in view of some specific features of the treatment needs of people living with addiction problems (e.g., accessibility to treatment, stigmatisation, high drop-out rate, etc.). In this context, interventions applying artificial intelligence (AI) features can play a specific and important role in the future. Artificial intelligence has emerged as a promising tool for improving diagnostic accuracy, and its role in treatment approaches has also been examined in mental health care. Based on a systematic literature review, the current presentation provides a comprehensive overview and analysis of the already existing AI-based applications in addiction treatment and prevention and also examines the future potentials of these interventions.