This pilot examined how EdLight’s AI‐supported analysis of handwritten student work functioned within everyday classroom contexts, with a focus on instructional decision‐making, time use, and alignment with teachers’ professional judgment. Middle school math teachers used EdLight to analyze exit tickets and student work artifacts as part of their regular instructional routines.

Data sources included weekly teacher logs, post‐pilot surveys, and teacher empathy interviews. Findings indicate that EdLight enhanced teachers’ instructional sensemaking and efficiency when insights aligned with curriculum pacing and classroom realities. Teachers consistently valued the tool’s ability to surface patterns across student work, supporting quicker grouping decisions and more focused planning.

Pre/post survey data indicated a shift from approximately 45 minutes per class to 15-30 minutes for most teachers, reflecting reclaimed instructional planning time and faster access to actionable insights. The pilot also surfaced important design insights about when AI‐generated feedback is most actionable in practice.