The proliferation of generative artificial intelligence (AI) has initiated a seismic shift in American higher education, forcing a reevaluation of established instructional models. While traditional digital tools acted as static resources, current AI systems actively synthesize information, generate original content, and simulate human reasoning. Hristova (2025) observes that the United States maintains a distinct approach to these technologies compared to European or Chinese models, prioritizing rapid adoption alongside decentralized institutional autonomy. This technological surge arrives at a moment when universities face increasing pressure to modernize curricula while maintaining rigorous academic standards. The shift represents a fundamental change in how knowledge is constructed and validated within the academy (Meng & Luo, 2024). Despite the potential for personalized learning, the integration of AI introduces significant disruptions to pedagogical integrity and assessment vali