The Operational Gap in Educational AI Governance: A Landscape Analysis of International Frameworks
The rapid deployment of artificial intelligence systems in educational settings has prompted significant policy development from international bodies, regional regulators, and national governments. This memorandum examines the current landscape of AI governance frameworks applicable to primary, secondary, and post-secondary education, identifying a consequential gap between policy articulation and institutional implementation. Through systematic analysis of frameworks from UNESCO, the OECD, UNICEF, the European Union, and various national jurisdictions, this paper establishes a four-category taxonomy: aspirational frameworks (which articulate principles), regulatory frameworks (which establish legal requirements), sector guidance (which provides education-specific recommendations), and operational frameworks (which supply implementation infrastructure). The analysis reveals that while the first three categories have proliferated, operational frameworks capable of translating policy into documented, auditable institutional practice remain largely absent from authoritative sources. This gap has significant implications for institutional compliance, insurance liability, and the protection of student welfare. The paper concludes that the education sector requires purpose-built operational infrastructure to bridge the distance between governance principles and demonstrable practice. SSRN working paper record will be added when available.
Authors
- Ryan James Purdy
Institutions
- House Clinic (US)
- SinoMaps Press (CN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-12-21
- DOI
- https://doi.org/10.5281/zenodo.18007386
- Primary Topic
- Global Educational Policies and Reforms
- Type
- article
- Field-Weighted Citation Impact
- 0.00