Capacity and Disposition: A Framework for Understanding GenAI Engagement in Assessment Practice

Generative artificial intelligence (GenAI) has made assessment work faster, messier, and more consequential. This conceptual article argues that assessment professionals’ engagement with GenAI is shaped less by simple enthusiasm or resistance than by the relationship between two conditions: the time professionals have to learn, test, and implement AI responsibly, and the disposition they bring to AI-mediated assessment practice. Institutional support functions as the environment that expands or constrains both. The article proposes the Capacity-Disposition Framework, a model that identifies four engagement conditions: The Calendar Trap, The Margin Lab, The Evidence Gate, and The Practice Commons. The framework helps assessment leaders diagnose uneven AI adoption, protect time for meaningful experimentation, honor appropriate skepticism, and connect AI use to validity, equity, transparency, and continuous improvement rather than speed alone.