Last updated: March 2026
Dimension 4 of 9
Policy & Governance
Policy and governance encompasses the formal documented rules, decision-making structures, and review processes that govern AI use in a school. This includes AI-specific acceptable use policies, data governance for AI tools, review and update cycles, stakeholder consultation, and the governance machinery that ensures policies remain current and effective.
Why this matters
Without clear AI policy, schools are exposed to significant risk. Staff and students may be using AI tools without guidance, potentially entering sensitive data into third-party systems, using AI in assessment contexts without clear rules, or making inconsistent decisions about acceptable use. The absence of policy does not mean the absence of AI use — it means AI use is ungoverned. In the international school context, policy complexity is amplified by multiple jurisdictions, curricula, and governance structures.
The 5 maturity levels
Schools progress through five maturity levels, from initial exploration to sector leadership. Each level builds on the previous one.
Level 1: Exploring
Interim guidance
No AI-specific policies exist. The school may have general technology policies but these do not address AI tools or AI-specific risks.
Key indicators
- No AI-specific policy document
- No AI acceptable use guidelines
- No governance framework for AI decisions
- No data governance specific to AI tools
Level 2: Developing
Dedicated AUP
Generic technology policy that mentions AI incidentally. AI may be referenced without specific, actionable guidelines.
Key indicators
- Technology policy exists but AI mentioned only in passing
- No dedicated AI section or guidance
- No specific data governance for AI
- Policy does not address generative AI specifically
Level 3: Established
Governance committee
Dedicated AI acceptable use policy with clear guidelines. The school has AI-specific policies addressing acceptable use, data governance, and key considerations.
Key indicators
- Dedicated AI acceptable use policy
- Clear guidelines on approved AI tools
- Data governance addressed
- Different guidelines for staff and student AI use
Level 4: Advanced
Annual review
Comprehensive AI governance framework with regular review. AI governance is embedded in the school's governance structures with clear decision-making processes.
Key indicators
- Regular review cycle (at least annual)
- Stakeholder consultation in policy review
- AI tool approval/procurement process
- Incident response procedures for AI issues
Level 5: Leading
Published model
AI governance model is exemplary with stakeholder involvement. The school's governance is a model for others with proactive policy development.
Key indicators
- Governance model shared externally
- Proactive policy development
- Student and parent voice in governance
- Governance informed by multiple international frameworks
What we look for
When auditing this dimension, we examine your school’s documents for evidence across these key areas:
An AI-specific acceptable use policy
Clear data governance policies for AI tool usage
Regular policy review and update cycles
Stakeholder consultation (parents, students, staff) on AI policy
Framework alignment
This dimension is benchmarked against leading international frameworks to ensure your audit reflects global best practice.
UK DfE Generative AI Guidance
Department for Education guidance for schools on the safe and effective use of generative AI tools.
EU AI Act
Comprehensive European regulation establishing requirements for AI systems based on risk classification.
NIST AI Risk Management Framework
US framework providing guidance for managing risks associated with AI systems across their lifecycle.
ISO 42001
International standard for AI management systems, providing a framework for responsible AI governance.
Common gaps
These are the most frequent gaps we see when auditing schools in this dimension:
Banning AI tools entirely — unenforceable and counterproductive
Copying another school's policy without contextualisation
Writing policy without consulting teachers, students, or parents
Treating policy as a one-time document rather than a living framework
Ignoring data governance — what data may be entered into AI tools
Failing to distinguish between staff and student AI use
How this connects to other dimensions
No dimension exists in isolation. Understanding these connections helps schools prioritise their improvement journey.
Depends on Institutional Readiness — leadership mandate and resources for policy development
Enables Assessment Integrity — assessment policy for AI requires governance foundation
Enables Ethical Framework — ethical principles are operationalised through policy
Enables Safeguarding & Risk — safeguarding policies build on the AI governance framework
Find out your school’s policy & governance score
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