From program pages to AI answers: Creating content students can find

This session explores how UT San Antonio built a scalable AI optimization (AIO) framework to strengthen the discoverability and relevance of academic program content across AI search experiences, language models and next-generation answer engines. The framework focuses on structured content, cross-college collaboration and AI-supported content workflows that center on what students most want to know when researching academic programs.

You’ll learn how UT San Antonio partners with colleges and faculty to create consistent, AI-friendly content at scale. This includes program-level FAQs that reflect real student intent and structured markup that improves clarity for AI systems and human visitors to the admissions website.

You’ll learn:

• How to coordinate with colleges to produce standardized, AI-discoverable FAQs rooted in student search behavior.
• How structured markup and richer content signals can improve program-page visibility in answer engine optimization.
• How to build content-creation workflows that use AI and data insights to accelerate production while maintaining academic accuracy.
• How to work with a digital marketing partner to track your share of AI answers and keyword visibility.
• How this work can support broader content-modernization efforts.

You’ll leave with practical tips for building scalable AIO processes, creating content aligned with student needs and preparing program pages for an AI-dominant search environment.

Presenter

Scott Glavac — The University of Texas at San Antonio