The integration of computational intelligence within American classrooms has transitioned from a speculative future to an immediate operational reality. Recent comparative analyses demonstrate that US institutions are increasingly prioritizing automated pedagogical tools to bridge achievement gaps, particularly in secondary literacy programs (Schrag & Short, 2025). Such acceleration is not merely a technical upgrade; it represents a fundamental reconfiguration of the relationship between instructor and learner. As Basch and Hillyer (2025) observe, college students now utilize these systems for personal, coursework, and classroom applications with unprecedented frequency. Widespread adoption necessitates a rigorous examination of how these tools redefine academic rigor and institutional standards. Despite the promise of enhanced efficiency, the rapid deployment of generative models introduces systemic vulnerabilities that current regulatory frameworks are ill-equipped to manage. Dispari