Becoming the Source AI Cites: GEO Best Practices for Higher Education

Prospective students are increasingly asking AI tools which programs, schools, and degrees are right for them. But even when an institution performs well in traditional search, AI tools may rely on rankings sites, aggregators, or other third-party sources instead of the university itself.

Higher education faces a particular challenge. Program information is often spread across central websites, colleges, departments, and other institutional domains, while third-party sites package the same information in a way that is easy for AI systems to find and cite.

In this session, RDA and Michigan State University will share practical approaches for improving visibility in AI search. The discussion will cover how to strengthen program content, establish clearer authority across decentralized sites, create governance that can scale across a large institution, and measure whether those efforts are improving AI visibility over time.

Key takeaways:

• How AI is changing higher-ed discovery: Where AI search fits alongside traditional search, why strong SEO does not automatically translate into AI visibility, and what institutions should begin measuring differently.
• What makes a program page more citable: The content, structure, language, and supporting information AI systems need to confidently use institutional pages when answering questions about programs, admissions, cost, format, and outcomes.
• How to establish authority across a decentralized institution: How to reduce competing answers across central, college, department, and program sites while preserving the flexibility distributed teams need to manage their content.
• How to govern and measure AI visibility at scale: How shared standards, repeatable page patterns, ownership, and ongoing measurement can help institutions improve visibility across hundreds of programs and contributors, with MSU as a working example.

This Webinar airs at 12 PM CST and will be available on-demand for six months after airing.