CASE Insights on Generative AI in Advancement-Presentation

Presentation

Pdf Summary

The Council for Advancement and Support of Education (CASE) conducted research in 2024-2025 on the institutional use of generative AI within educational advancement functions. This research included online trainings with CASE members, focus groups, and leadership interviews aiming to understand adoption trends, challenges, and benefits. Key insights show that most generative AI use to date has been by individuals or small teams, primarily intended to enhance efficiency rather than the efficacy of advancement activities. Adoption is typically led by Marketing & Communications departments, often utilizing third-party vendor tools or paid models. Institutional support through training, policies, and cross-functional committees is emerging but still limited. Leaders are often waiting for institutional direction or new vendor solutions, though some have begun deeper investments. Effective AI initiatives rely not only on technology but also on an institutional culture willing to innovate and experiment.<br /><br />The research highlights the importance of enabling safe and personalized learning environments for leadership and staff to explore AI’s potential. Other departments such as Research and IT often lead AI adoption efforts. CASE encourages institutions to engage interdisciplinary teams to assess their AI readiness and provides an interactive report and benchmarking cohort opportunities to advance AI strategy in advancement. The CASE Gen AI Benchmarking Cohort offers practical training, strategic assessment, and a collaborative environment for AI ambassadors, leadership champions, and innovation drivers to build capabilities and communicate successes.<br /><br />Recommendations include carving out time to explore CASE’s interactive resources, assembling cross-functional teams for assessment, and participating in CASE’s structured learning and benchmarking cohort to efficiently integrate AI tools and shift from efficiency-driven to efficacy-driven AI use in advancement. Overall, institutional flexibility, leadership engagement, and cultural openness are critical for successful generative AI adoption in education advancement.

Keywords

Generative AI

Educational Advancement

CASE Research

AI Adoption Trends

Marketing & Communications

Institutional Support

AI Training

Cross-functional Teams

AI Benchmarking Cohort

AI Strategy