The Compliance Target Is Moving. So Is the Ground Under It.
Education AI mandates set fixed deadlines while the infrastructure underneath, vendor by vendor, is being actively rearchitected in real time.
Education AI mandates set fixed deadlines while the infrastructure underneath, vendor by vendor, is being actively rearchitected in real time.
A wave of district-level AI policy adoption is outrunning the data governance infrastructure needed to make those policies legally enforceable under FERPA and state privacy law.
Florida and Trinity College Dublin issued classroom AI policies, but neither defines the infrastructure, vendor, or data boundary that governance frameworks require.
Instructor-level AI policies solve academic integrity optics but leave the actual FERPA exposure, student data flowing into third-party tools, largely unaddressed.
New York City's mandate to write K-12 AI guidelines in a year, not a biometric-data lawsuit, is the forcing function classroom AI tools now face.
As colleges route student data through AI tools for advising and administration, FERPA and state privacy laws expose a vendor accountability gap that conduct policies don't touch.
Three governance models for campus AI policy expose the same gap: no named accountable owner for tool approval and student data handling.
Florida ordered every school and college to write AI policy by 2027, but the harder problem is vendor data governance, not policy language.
Florida's July 2027 deadline for AI policies in K-12 and state colleges forces education leaders to build verifiable governance, not just guidance documents.
State AI rules are proliferating while FERPA leaves a data gap, forcing districts to govern hundreds of ed tech vendors on their own.