Navigating GenAI in assessment design with supercharging and proofing

The emergence of generative AI (GenAI) has introduced a shift in higher education, reshaping how instructors approach teaching, how students engage with learning, and, most importantly, how learning is assessed. As these technologies become increasingly integrated into educational contexts, established assumptions about assessment design are being actively questioned. In this paper, we provide a brief overview of differing perspectives on GenAI integration in assessment design. We introduce the AI-supercharging and AI-proofing (ASAP) framework as a practical approach to rethinking assessments in ways that maintain and prioritize core learning objectives while leveraging GenAI to deepen student learning. We describe the design and implementation of a faculty-facing workshop that uses this framework to foster reflective conversations about assessment and academic integrity and provide facilitation resources and examples that others can adapt in their own contexts. We describe our evaluation of the workshop efficacy and share observations of how these workshops lead to shifts in faculty perspective. The workshop inspires enhanced willingness to adopt GenAI and leads to a more positive, nuanced view of its use in the classroom. We also discuss lessons learned from facilitating these workshops and fostering productive, reflective discussions within teaching and learning communities. In addition, we provide a guided worksheet designed to support educators who are hesitant about adopting AI, offering a step-by-step resource for rethinking an assessment. Our experiences suggest that engaging with the ASAP framework supports educators in redesigning more meaningful, well-aligned assessments while integrating GenAI thoughtfully and moving beyond initial hesitancy.