Predicting financial market stress is a significant challenge, as traditional models often fail to capture complex and nonlinear dynamics. This column highlights two recent advances in the use of AI tools to anticipate financial market stress. The first is a novel framework using machine learning to predict financial market stress and explain the main factors driving predictions. The second integrates numerical data with textual information using large language models to forecast market stress and identify its underlying drivers. Policymakers can use these tools to monitor emerging risks in real time, combining quantitative forecasts with qualitative insights from financial news and commentary.