AI Isn’t Breaking Assessment: It’s Fixing It!

Artificial intelligence is often seen as a threat to student learning, with common concerns about academic integrity, erosion of skills, and the validity of assessment. This dominant narrative obscures a more complex, and ultimately more productive, reality. Emerging evidence suggests that AI is not undermining assessment so much as exposing long-standing weaknesses in how assessment has been designed and implemented. This session highlights the EDUCAUSE Impact of AI on Learning Assessment study, with insights from frontline higher education practitioners. The study examines attitudes, policies, evolving assessment practices, and promising approaches emerging across institutions. We will reframe AI as a catalyst for returning to the foundational purposes of assessment: supporting learning, demonstrating authentic understanding, and aligning evaluation with meaningful outcomes. Attendees will engage with key findings, emerging patterns, and promising practices that highlight how institutions are moving beyond reactive responses toward intentional learning-centered redesign. This is not a report-out, but rather a forward-looking conversation. Attendees will leave with practical perspectives for shifting from fragmented responses to more intentional aligned approaches to assessment in an AI-enabled landscape.