Making AI Work: A Framework for AI Facilitation across the Project Life Cycle

As higher education institutions accelerate the adoption of artificial intelligence (AI), researchers, educators, and IT leaders face growing challenges in navigating the full AI project life cycle—from problem formulation and data preparation to model development, deployment, and long-term sustainability. Research Computing and Data (RCD) professionals are uniquely positioned as institutional AI facilitators, yet few shared frameworks exist to guide that role. This session introduces an AI Facilitation Taxonomy, a practical framework developed by the Campus Research Computing Consortium (CaRCC) AI Facilitation Materials Working Group. It maps each project life cycle stage to user needs, common tasks, required tools, and the critical facilitation role that Research Computing and Data (RCD) teams play. Through a use-case walkthrough, we demonstrate how RCD professionals apply the taxonomy to guide AI practitioners from initial scoping to scalable deployment; where RCD expertise adds the most value; how to anticipate common challenges at each project stage; and how to navigate the organizational, technical, and compliance and governance issues. Designed for RCD professionals, IT leaders, and AI practitioners in higher education institutions, this session offers actionable approaches to facilitate AI in education, research, and institutional operations, applicable across institution sizes and resource levels.