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Campus AI Development · Building software with AI in higher education
A field guide for colleges and universities. Four steps take a project from an idea to the right approach and controls. Everything else is reference.
The strictest answer wins. At step 4, six questions and the data level each point to an approach; the most demanding one sets the approach and its minimum controls.
↺ When a project grows (new users, more sensitive data, funding, decisions about people), go back to step 2.
Software on campus used to come from a few developers in IT. Now an advisor, a faculty member or a first-year student can build a working tool in an afternoon. This guide helps decide how to build the thing in front of you, with the governance higher education requires. It is a set of recommendations, not a mandate or legal advice.
“Our students are not asking permission to use AI.”
A higher education executive
Nor are our campus community members asking permission to develop with AI.
The question for institutions is no longer whether people will build, but how to help them build well.Where this fits
A companion to the Campus AI Framework
The Campus AI Framework sets the institutional operating model: eight pillars for strategy and governance, four application domains and the AI Strategic Compass for prioritization. Once an initiative is worth pursuing, this guide helps decide how to build it. It goes deeper on the homegrown, in-house pathway and on the Campus Readiness and Implementation & Operations pillars. Both are starting points to adapt locally, not mandates.