The Standard
The Certiva AI-Ready Standard
The criteria a school must satisfy to be accredited AI-Ready — criterion-referenced, evidence-based and developmental. Applies to K–12 schools of any type.
Alignment
Built on the world’s leading frameworks
The Standard is aligned with the UNESCO AI Competency Framework, the ISTE Standards for Educators & Leaders, the OECD AI Principles, and the education provisions of the EU AI Act — applied as a complement to, not a replacement for, national regulation.
Six domains
What accreditation assesses
Each domain contains criteria scored on a four-point scale. All six must reach “Established” for accreditation.
Leadership & Strategy
AI vision, strategic plan, governance ownership, and resourcing.
- A documented, board-endorsed AI vision and multi-year strategic plan.
- A named senior leader owns AI strategy; an AI steering committee meets regularly.
- The Head plus at least two senior leaders hold the Certiva AI Leader Certificate.
- AI investment is planned and justified against defined outcomes and a budget.
Governance, Ethics & Risk
AI policy, risk management, ethics oversight, and legal compliance.
- A comprehensive, published AI policy governs staff and student use.
- An AI risk register with owners and mitigations, reviewed at least annually.
- An ethics oversight process evaluates AI use cases.
- Legal and regulatory obligations (GDPR, EU AI Act, local law) are mapped and met.
Educator Capability
Teacher and leader certification coverage and classroom competence.
- At least 80% of teaching staff hold the AI Teacher Certificate (Level 2).
- Certification is current and evidenced on the school dashboard.
- Teachers demonstrate AI competence in observed practice, not only on paper.
- Ongoing AI professional learning (PLCs, coaching, or an AI Coach) is in place.
Teaching, Learning & Assessment
AI-enhanced pedagogy, personalisation, and integrity-aware assessment.
- AI is integrated into lesson and unit design where it adds pedagogical value.
- AI personalises and differentiates learning for diverse learners.
- Assessment design accounts for AI — valuing process and using AI-resistant methods.
- Human judgement remains central; AI supports but does not replace the educator.
Data Protection & Safeguarding
Data governance, privacy, security, and student safeguarding with AI.
- A data governance framework covers AI tools, including data-flow mapping and vendor due diligence.
- AI tools are vetted for privacy, security and age-appropriateness before adoption.
- Safeguarding policies explicitly address AI (content, contact, conduct, wellbeing).
- Data protection roles, retention and breach procedures are defined and understood.
Student AI Literacy & Wellbeing
Student curriculum, equitable access, digital citizenship, and wellbeing.
- Students receive age-appropriate AI literacy education.
- Access to AI learning is equitable across student groups.
- Students understand responsible, honest AI use (digital citizenship & integrity).
- Student wellbeing and healthy technology use are actively supported.
Scoring
Four readiness levels
Each criterion is scored on a four-point scale. “Established” is the accreditation threshold.
Emerging
Little or no evidence; ad hoc or absent practice.
Developing
Practice is beginning but inconsistent or incomplete.
Established
Consistent, embedded practice with clear evidence.
Leading
Exemplary, innovative practice that could inform the field.
Preparing for accreditation?
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