This study investigates the substantial impact of generative artificial intelligence (AI) on teaching effectiveness in higher education, emphasizing its transformational function in knowledge management (KM) processes. Despite prior research acknowledging AI’s transformative potential in education, the complex mediating processes, particularly those associated with generative models, remain little explored. The resource-based view (RBV) ideology primarily seeks to elucidate how Generative AI-driven information management improves educational results. We employed a quantitative methodology to conduct a structured survey among academics and administrators in higher education. Structural equation modeling was utilized to analyze the collected data. Our research demonstrates that Generative AI significantly improves knowledge management processes, including the creation, curation, and dissemination of educational information, leading to a substantial enhancement in pedagogical effectiveness. The ability of generative AI to produce customized instructional materials, automate content summarization, and facilitate dynamic knowledge synthesis has shown to be crucial. The strategic integration of Generative AI into higher education, through robust and adaptable knowledge management frameworks, is essential for enhancing educational efficacy. These findings underscore the necessity for educators and policymakers to prioritize the development of Generative AI-enabled knowledge management strategies to fully use the potential of AI in revolutionizing the future of education.