Last updated: March 2026
Dimension 8 of 9
Technical Infrastructure
Technical infrastructure encompasses the central provisioning and management of AI tools, security controls governing AI access, usage monitoring and logging, and content filtering and safety measures. This dimension assesses the technical foundation that enables safe, managed AI use across the school.
Why this matters
Without appropriate infrastructure, AI use is either blocked entirely or — more commonly — happens in an unmanaged, unmonitored way through personal accounts and devices. This represents the highest risk profile: unmanaged AI use with no institutional controls. Schools need to move from blocking or ignoring AI to actively managing it through approved tools, access controls, monitoring, and content filtering.
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
Audit existing usage
No AI-specific technical infrastructure. The school has not provisioned any AI tools centrally. Any AI use is through personal accounts.
Key indicators
- No approved AI tool list
- BYOD AI usage without oversight
- No SSO integration for AI tools
- No monitoring of AI tool usage
Level 2: Developing
Approved tools with SSO
Basic internet access but no AI tool provisioning. Infrastructure supports access but the school has not specifically managed any AI tools.
Key indicators
- Internet access supports AI tool use
- No centrally approved AI tool list
- No institutional licensing for AI tools
- IT department aware but not actively managing
Level 3: Established
Monitoring and logging
Approved AI tools provisioned with SSO and access controls. The school has formally approved and provisioned AI tools with appropriate access controls.
Key indicators
- Approved AI tool list published and communicated
- SSO or institutional accounts configured
- Access controls appropriate to age and role
- Tool approval process exists for new tools
Level 4: Advanced
Content filtering
Managed AI platform with monitoring, logging, and content filtering. Active monitoring, logging, and content filtering protect students.
Key indicators
- Usage monitoring and logging active
- Content filtering applied to AI tools
- Analytics providing insight into usage patterns
- Regular security reviews of AI configurations
Level 5: Leading
API integrations
Enterprise-grade AI infrastructure with API management and security. Advanced infrastructure supporting custom integrations and innovation.
Key indicators
- API-level integration of AI tools into school systems
- Custom AI applications for school-specific needs
- Advanced security with active threat monitoring
- IT team has demonstrable AI-specific expertise
What we look for
When auditing this dimension, we examine your school’s documents for evidence across these key areas:
AI tools centrally provisioned and managed
Appropriate security controls for AI tool access
AI tool usage monitored and logged
Content filtering and safety measures applied to AI tools
Framework alignment
This dimension is benchmarked against leading international frameworks to ensure your audit reflects global best practice.
NIST AI Risk Management Framework
US framework providing guidance for managing risks associated with AI systems, including security and monitoring.
ISO 42001
International standard for AI management systems, covering infrastructure, security, and governance requirements.
CoSN/CGCS AI Maturity Tool
Consortium for School Networking tool assessing technology infrastructure maturity for AI in education.
Singapore AI Governance Framework
National framework addressing technical governance of AI systems including security, monitoring, and access control.
Common gaps
These are the most frequent gaps we see when auditing schools in this dimension:
Blocking AI tools entirely — students use them on personal devices regardless, removing institutional oversight
Not auditing shadow IT — failing to discover what AI tools are already in use
Provisioning tools without training — infrastructure without PD is wasted investment
Ignoring content filtering for AI — students accessing unfiltered AI content on school networks
Not considering data residency and processing requirements
Over-engineering infrastructure before understanding actual needs
How this connects to other dimensions
No dimension exists in isolation. Understanding these connections helps schools prioritise their improvement journey.
Depends on Institutional Readiness — budget and strategy must support infrastructure investment
Enables Teacher AI Competency — tools must be available before teachers can develop competency
Enables Student AI Literacy — students need access to managed, safe AI tools
Enables Safeguarding & Risk — technical controls are a key layer of safeguarding
Find out your school’s technical infrastructure score
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