AI tutors, proctoring, admissions analytics and campus GenAI all touch student records and high-stakes decisions. Asenion turns student privacy, security and accessibility requirements into operational controls your CISO, privacy office and academic leaders can test, monitor and evidence.
Schedule a Call30 minutes with our AI compliance team.
Few of these were written only for AI. All of them apply to it.
Protects education records at schools and institutions that receive federal funding.
For AI:AI tools processing student records need a valid FERPA exception, contract limits on use, and no training on student data without authorization.
FTC rule on collecting personal information from children under 13, with amendments finalized in 2025.
For AI:K-12 AI tools need consent or school authorization, data minimization, retention limits, and separate consent before children's data goes to third parties.
Required of institutions in federal student aid programs and reviewed through Federal Student Aid audits.
For AI:AI tools touching financial aid or student account data fall under your written information security program, risk assessment and vendor oversight.
AI used for admissions, evaluating learning outcomes, assigning education levels or monitoring students during tests is high-risk. Under the AI Omnibus, those obligations apply from December 2027.
For AI:Risk management, data governance, human oversight and transparency for admissions, grading and proctoring AI.
DOJ rule requiring public colleges, universities and school districts to meet WCAG 2.1 AA for web content and mobile apps.
For AI:AI tutors, chatbots and AI-generated course content delivered to students must be accessible.
The AI use cases we see most often, and the requirements that follow them.
Tutors must keep student data out of vendor training, give age-appropriate responses and work for students with disabilities.
Models that rank applicants or flag at-risk students need bias testing, transparency and a human decision-maker.
These tools can produce false accusations and collect biometric data. They need accuracy testing, appeal paths and privacy controls.
Faculty and staff GenAI use needs data classification rules, approved tools and controls for sensitive and controlled research data.
One set of controls, applied from vendor review through runtime, with evidence your auditors, boards and families can rely on.
Start from Policy Packs for FERPA, COPPA, the GLBA Safeguards Rule and the EU AI Act, combined with your institution's own AI use policy.
Test tutors, chatbots and decision models for bias, age-inappropriate content, student data leakage and prompt injection, with every result mapped back to a control.
Apply context-aware controls to AI agents in production and capture tamper-resistant evidence of what happened, which controls applied and whether they worked.
In 30 minutes we'll map your AI tools and use cases to the rules above, show the controls that apply, and point out gaps in your AI governance.
Schedule a CallNo preparation needed.
