Generative AI is rapidly reshaping teaching, learning and operations across higher education, creating new opportunities for innovation while challenging established practices in assessment, policy, and equity.
This webinar explores ideas on how institutions can integrate AI responsibly while supporting instruction and academic integrity. It considers policy and practice at three levels — institution, department/program and course — so leaders and instructors can set clear expectations as technologies evolve. The session also addresses equity concerns, including differential access to tools, resource constraints and algorithmic bias, and how these factors shape student experience and outcomes.
Participants will leave with actionable strategies and a governance-oriented perspective they can apply immediately: where to pilot, how to set disclosure norms and assessment practices, and how to track impact on learning, workload and fairness.
Key takeaways
- A practical governance model that clarifies roles and decision rights at the institution, department/program and course levels — usable across colleges and universities
- Clear policy and disclosure norms for acceptable AI use by students, instructors and staff, with adaptable syllabus language and review cadences
- Assessment and course design strategies (process evidence, staged drafts, authentic tasks, brief oral/interactive checks) that promote higher-order learning and limit misuse without relying on AI detectors
- An equity and risk checklist for pilots and scale-up: access and affordability, discipline-specific needs, privacy/bias safeguards and a compact set of indicators to monitor effects on learning, integrity and workload.
