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Artificial intelligence has entered the K-12 classrooms faster than schools have been able to respond, leaving teachers to figure out what to do with it on their own. This study draws on thirty in-depth interviews with public school teachers teaching grades 6 through 12 to examine how teachers make sense of and respond to AI in the absence of formal policy guidance, and what that variation reveals about the organizational conditions of their schools. Drawing on Lipsky’s theory of street-level bureaucracy and Weick’s theory of sensemaking, I find that teacher variation in AI does not reflect their individual dispositions or technological skills, but rather their structural position. What teachers have access to in their schools, from professional development, and administrative support to collegial networks and material resources, shapes the sensemaking resources they can draw on. Leading to three patterns: organizational enablement, organizational constraint, and precarious discretion. I argue that loose coupling, which has been treated as a neutral or even functional feature of school organization, operates in the AI context as a mechanism of inequality distributing discretionary space unevenly across organizational contexts and leaving students with very different relationships to a technology that is rapidly reshaping education.