Large language models can supplement the assessment of clinical high risk for psychosis.

s < .001). In exploratory analyses, decoder-generated risk scores incrementally improved models predicting conversion including SHARP but not NAPLS risk scores. Although our results need to be considered in the context of one consortium, AI-based NLPs show potential as an aid for the diagnosis of CHR syndromes, evaluating psychosis risk, and even predicting future conversion, even with suboptimal but readily available inputs (i.e., assessor notes). Future projects could use AI-based tools' potential in augmenting psychosis risk screenings and risk predictors. (PsycInfo Database Record (c) 2026 APA, all rights reserved).