From pilot to campus-wide AI: lessons from a university that scaled it

A candid conversation on what it takes to move AI from proof-of-concept to core campus infrastructure.

Most AI pilots in higher education fail quietly. The technology works, but the rollout does not. Governance questions go unanswered, departments resist, and the project stalls before it reaches scale. Getting from a working prototype to campus-wide infrastructure is as much an organizational challenge as a technical one, and most institutions are not prepared for both.

The University of Lynchburg solved it. Their AI agent started with a single use case and expanded to cover admissions, IT, athletics, and academic services – connecting to existing content and systems without rebuilding the technology stack. It surfaced data quality issues leadership did not know existed, handled 80+ student messages before 9 a.m. every day, and eliminated more than $500,000 in annual technology costs.

This webinar features the university leaders who ran the rollout, with candid detail on governance decisions, integration approach, stakeholder resistance, and the phased roadmap that got them to scale.

You’ll learn:

 

• How to govern AI deployment across departments without slowing time-to-value
• The integration approach that worked without a tech stack rebuild
• How to bring skeptical stakeholders on board before the rollout