Abstract
Recent advances in artificial intelligence (AI) have transformed scientific innovation across multiple disciplines. However, within prevention science, AI has been used primarily for risk detection, leaving its potential to enhance program implementation largely unexplored. This dissertation provides empirical evidence that AI, particularly Generative AI, can play a transformative role in implementation science. Three studies are presented to demonstrate this potential. Study 1 developed an AI-driven chatbot that simulates adolescent participants to support facilitator training in a brief preventive intervention. Study 2 evaluated the validity and reliability of an AI-based system for automatically identifying and coding facilitator delivery skills to assess implementation fidelity. Study 3 generated an automated feedback report translating AI-coded data into actionable insights for facilitators. Together, these studies advance prevention science by demonstrating practical and ethical approaches to integrating AI into the implementation of preventive interventions. This research strengthens implementation practices, bridges the gap between technological innovation and real-world application, and ensures that AI-driven tools make meaningful contributions to prevention science.