The rapid expansion of the Fourth Industrial Revolution has catalyzed a profound restructuring of American pedagogical frameworks, moving beyond simple digitization toward a fundamental reconfiguration of instructional logic. OKunlola and Naicker (2025) observe that the convergence of post-pandemic digital acceleration and advanced computational capabilities has pushed educational institutions into an era of unprecedented technological reliance. Unlike previous instructional shifts, the current integration of Artificial Intelligence (AI) does not merely supplement existing methods; it redefines the fundamental relationship between learner, instructor, and institutional governance. This transformation manifests through the deployment of Large Language Models and adaptive learning algorithms that promise personalized instruction while simultaneously introducing systemic risks regarding data integrity and social equity. The speed of this adoption often outpaces the development of robust e