From policy on paper to practice in the classroom
AI use is already happening across your institution. Coordinated governance often isn’t. We map what is actually happening across three layers, score your readiness, and deliver a prioritized action plan.
The gap
Senior leadership publishes broad guidance. IT manages tools and risk. Instructors set their own classroom rules. The result is a gap between institutional policy and what actually happens in teaching, assessment, grading, and student work.
Why now
Universities are moving quickly from informal experimentation to questions of accountability, academic integrity, learning outcomes, faculty practice, and institutional risk. That is rarely solved by publishing another broad policy.
What the gap costs you
- Inconsistent expectations for students across courses and faculties
- Unclear ownership across academic leadership, IT, instructors, and student success
- Uncertainty about acceptable use in teaching, assessment, grading, and feedback
- Policies that exist formally but are hard to implement consistently
- Difficulty preserving critical thinking when AI is embedded in the workflow
The assessment
- Map current AI use and decision-making across the three layers
- Identify the gap between institutional policy and classroom practice
- Clarify ownership, escalation paths, and unresolved decisions
- Assess readiness across governance, adoption, capability, risk, and implementation
- Produce a practical maturity score
- Deliver a prioritized action plan matched to your context and level of AI adoption
Most institutions can describe Layer 03. Very few can describe Layer 01.
Why Northlight
An agile advisory engagement for institutions that need a clear diagnosis and practical next steps before committing to a large transformation program. We combine academic and teaching experience with hands-on AI literacy, governance, workflow, and implementation work.
Start with a 30-minute conversation
We begin with the person closest to the problem — typically a provost-level, senior academic, student-success, or academic technology leader. We use that conversation to understand where AI decisions currently sit, what is happening in practice, and whether a readiness assessment would be useful.