Artificial intelligence holds great promise for advancing psychological science, particularly in research with clinical populations. However, its use also introduces unique complexities that require careful consideration. This presentation will bring to the symposium perspectives grounded in translational science and experimental psychopathology. Drawing from this work, the presentation will highlight both the opportunities and the challenges of incorporating AI into studies with clinical populations. Particular attention will be given to the nuances of applying AI tools in contexts where symptom expression and cognitive functioning may affect data quality, interpretation, and participant experience. The presentation will explore issues such as the accuracy and reliability of AI-derived measures, potential biases introduced by training data that do not adequately represent clinical groups, and the ethical implications of using adaptive or predictive AI systems with individuals experiencing psychological distress. The presentation will also discuss how AI may help refine experimental designs, improve measurement precision, and generate new insights into the cognitive mechanisms underlying psychopathology—while simultaneously underscoring the importance of researcher expertise and ethical vigilance. Finally, the presentation may also touch on potential considerations related to AI when translating this work into the community. Attendees will gain a deeper understanding of the methodological and ethical challenges inherent in applying AI to clinical research, as well as practical strategies for responsibly leveraging AI to advance the study of depression, anxiety, and related disorders.