The rapid proliferation of generative artificial intelligence has disrupted traditional educational frameworks, necessitating a rigorous re-evaluation of pedagogical standards. Montiel and Kundu (2025) observe that major educational groups in the United States are increasingly integrating these tools, yet this adoption often outpaces institutional readiness. Unlike previous technological shifts, the current AI wave directly challenges the cognitive labor of writing and analysis, which are the cornerstones of American higher education. This disruption is not merely technical; it is institutional, affecting everything from faculty compensation (Tran & King, 2024) to the fundamental way secondary literacy is taught (Schrag & Short, 2025). Despite the enthusiasm surrounding "personalized learning," a profound tension exists between technological innovation and academic integrity. Basch and Hillyer (2025) indicate that while students frequently utilize AI for personal and coursework applica