"AI makes this faster" is not enough information to decide whether a workflow is better. Faster for the instructor can sometimes mean more confusing for the student. Easier for a department can create another step for faculty. More automated can also make a process less accessible or harder to explain. When evaluating an AI workflow, consider everyone affected by it, not only the person operating the tool. Good implementation should reduce unnecessary friction without quietly moving that friction somewhere else.
Before adopting an AI workflow, ask three questions: Who saves time? Who gains work? What changes for the person receiving the result?
Have you encountered an "efficient" process that actually created more work for someone else?
Todays prompt: Evaluate this proposed workflow from the perspectives of the educator, learner, support staff, and institution: [DESCRIBE WORKFLOW]. Identify where it reduces work, where it may shift work to someone else, and any accessibility, privacy, clarity, or human-oversight concerns.