CASE Insights on Generative AI in Advancement-Presentation (Español)

Presentation (Español)

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The CASE Insights report from December 2025 presents research on the institutional use of generative AI within advancement functions in education. The research aims to guide advancement leaders on how generative AI might impact their work, identify realistic application pathways, understand organizational receptivity and adoption rates, and address ethical considerations such as data privacy, transparency, and equitable access in fundraising.<br /><br />The study involved multiple phases including online training in November 2024, participant surveys, case use data collection, asynchronous online focus groups in January 2025, and an in-person CASE 50 leadership discussion in February 2025. Key findings include that while most AI use remains at an individual or small-team level primarily for efficiency rather than effectiveness, marketing and communications departments lead adoption. Advanced users often leverage third-party vendor tools. Institutional support exists mainly through training, policy development, and exploratory committees. Leaders vary from those waiting for clearer guidance or vendor solutions to those actively investing and fostering a culture of innovation that embraces experimentation with new AI tools.<br /><br />The report emphasizes the need for safe, personalized learning environments for leadership as a critical component in progressing from efficiency to true effectiveness gains. CASE offers an interactive report and is launching a generative AI benchmarking cohort designed to help institutions evaluate their current adoption stage, prioritize implementation steps, build skills, explore state-of-the-art AI tools, and measure impact. Ideal participants include strategic leaders, AI innovation ambassadors, and key influencers who can drive adoption within their institutions.<br /><br />Overall, the CASE research highlights that successful generative AI integration in advancement is not just about technology but requires institutional flexibility, a culture open to innovation, and leadership support. The initiative encourages institutions to engage collaboratively to shape the future of AI-enabled advancement.

Keywords

Generative AI

Advancement Functions

Education

Institutional Adoption

Ethical Considerations

Data Privacy

AI Training

Leadership Innovation

AI Benchmarking

Fundraising Efficiency