AI Education in Higher Education: A Taxonomy for Curriculum Reform and the Mission of Knowledge

Artificial intelligence (AI) is reshaping higher education, yet current debates often feel tangled, mixing concerns about pedagogy, operations, curriculum, and the future of work without a shared framework. This paper offers a first attempt at a taxonomy to organize the diverse narratives of AI education and to inform discipline-based curricular discussions. We place these narratives within the enduring responsibility of higher education: the mission of knowledge. This mission includes not only the preservation and advancement of disciplinary expertise, but also the cultivation of skills and wisdom, i.e., forms of meta-knowledge that encompass judgment, ethics, and social responsibility. For the purpose of this paper's discussion, AI is defined as adaptive, data-driven systems that automate analysis, modeling, and decision-making, highlighting its dual role as enabler and disruptor across disciplines. We argue that the most consequential challenges lie at the level of curriculum and disciplinary purpose, where AI accelerates inquiry but also unsettles expertise and identity. We show how disciplines evolve through the interplay of research, curriculum, pedagogy, and faculty expertise, and why curricular reform is the central lever for meaningful change. Pedagogical innovation offers a strategic and accessible entry point, providing actionable steps that help faculty and students build the expertise needed to engage in deeper curricular rethinking and disciplinary renewal. Within this framing, we suggest that meaningful reform can move forward through structured faculty journeys: from AI literacy to pedagogy, curriculum design, and research integration. The key is to align these journeys with the mission of knowledge, turning the disruptive pressures of AI into opportunities for disciplines to sustain expertise, advance inquiry, and serve society.