IS THE AI DETERMINING ACCESS OR ADMISSION?
Annex III identifies certain AI systems used to determine access or admission to educational or vocational-training institutions and programmes as high-risk.
Education AI becomes high-stakes when it influences admission, placement, learning outcomes, assessment, access, or testing. The critical question is not whether software is used in a school—it is what decision the AI can materially influence and what evidence supports that use.
The Regulation identifies certain education and vocational-training AI use cases as high-risk, including access or admission, assignment to programmes, evaluation of learning outcomes, assessment of education level, and monitoring prohibited behaviour during tests. It separately prohibits certain emotion-recognition uses in education institutions except for medical or safety reasons.
Start with the actual system, role, use case and evidence boundary. The same regulation can produce different obligations for different actors and systems.
Annex III identifies certain AI systems used to determine access or admission to educational or vocational-training institutions and programmes as high-risk.
Systems intended to evaluate learning outcomes, assess an individual’s appropriate education level, or materially influence the level of education or training a person receives can also fall into the high-risk education category.
AI used to monitor or detect prohibited behaviour during tests is included among high-risk education use cases. Separate this from prohibited emotion-recognition uses in education institutions.
Preserve intended purpose, decision role, system version, data inputs, evaluation criteria, human oversight, appeal/escalation routes, testing, performance limits, notices, and changes affecting continued reliance.
The goal is not merely to reach an answer. It is to preserve what facts, evidence, scope and limitations supported that answer at that time.
Admission, placement, grading, learning-outcome evaluation, proctoring, tutoring, scheduling, recommendation, and administrative assistance should not be treated as one category. Classify the real intended purpose.
Map the system against Article 6 and Annex III, preserving unresolved facts and any claimed Article 6(3) exclusion instead of assuming every educational tool is automatically high-risk.
Connect data governance, technical documentation, logging, transparency, human oversight, accuracy, robustness, cybersecurity, review procedures, and appeal or escalation controls to the educational decision being influenced.
A tool that begins as tutoring support can become a materially different governance problem if it later ranks students, determines admission, changes placement, scores exams, or influences access to programmes.
Choose the smallest operating tier that fits the portfolio today. Upgrade when system count, team size or governance scope actually requires it.
Keep a living system-level evidence record with obligations, gaps, versions and revalidation state.
START EVIDENCE PASSPORT →Coordinate evidence, owners, documentation, incidents and team compliance work in one governed workspace.
START COMPLIANCE WORKSPACE →Operate broader high-risk, GPAI, FRIA, post-market and material-change governance across a growing portfolio.
START GOVERNANCE PRO →Run institutional governance with expanded users, authority workflows, examiner rooms and portfolio reporting.
START INSTITUTION →Use the free classifier to establish the system, intended purpose, possible actor role, EU exposure and unresolved facts. When continuing evidence infrastructure is needed, paid access begins at $19 per month. Independent human readiness review remains a separate service.
Certain AI systems intended to determine access or admission to educational or vocational-training institutions or programmes are listed in Annex III as high-risk.
Certain systems used to evaluate learning outcomes, assess appropriate education level, or materially influence the level of education or training a person receives are also included in the high-risk education category.
Certain AI systems intended to monitor or detect prohibited behaviour during tests are listed as high-risk in Annex III.
The AI Act prohibits certain emotion-recognition uses in education institutions, except where the use is intended for medical or safety reasons. This is a separate question from the Annex III high-risk education categories.
No. Classification depends on intended purpose. Administrative tools, general tutoring, content generation, scheduling, or other limited-support uses may follow different routes depending on what the system actually does and how it is used.
No. TA-14 can preserve system identity, classification basis, evidence, gaps, student-impact pathways, changes, and revalidation history. It does not itself provide legal advice, conformity assessment, certification, or regulatory approval.
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