Artificial intelligence is changing how universities search, summarize, analyze, and generate information. AI is powerful, which is perhaps why less experienced users are sometimes surprised by this limitation:

his piece tackles a problem that’s becoming more relevant as AI tools spread into everyday work: how do you check the quality of something an AI produced, when there’s no answer key to grade against?

Research administration is risk-averse on purpose. The work navigates federal regulations, sponsor-specific terms, institutional policies, and audit trails that survive personnel changes by years. RAs have been trained well, and the training has stuck: when in doubt, slow down; when the rule is unclear, ask; when the answer is unverifiable, do not submit. That posture is not a deficit to be retrained. It is an asset the institution already has, and it should be respected as such.