Most educational institutions recognize the need for AI governance but struggle to translate policy discussions into operational practice. Effective AI governance extends beyond creating acceptable use policies, it requires leadership structures, risk management, decision-making processes, stakeholder engagement, workforce readiness, and continuous oversight.

This session provides education leaders with a practical governance framework for implementing responsible AI across teaching, learning, administration, operations, and institutional decision-making. Participants will leave with a governance roadmap that enables innovation while protecting institutional integrity, privacy, security, and public trust.

Artificial intelligence is transforming every aspect of education, yet many institutions lack a structured governance framework to guide responsible implementation. Developing effective AI governance requires more than policies, it demands leadership, accountability, ethical decision-making, risk management, and continuous oversight. This session introduces a practical governance framework that education leaders can use to establish governance committees, define institutional AI principles, assess organizational readiness, manage risk, and develop implementation roadmaps. Drawing from executive leadership experience across education, government, and technology, attendees will gain practical tools to build responsible AI governance programs that foster innovation while protecting students, faculty, institutional data, and public trust.