School AI Readiness
Scorecard

No structured AI professional development has occurred. Teacher AI use is self-directed and ungoverned. There is no shared understanding of where AI assistance ends and professional judgment begins.

Some teachers have attended AI training, typically external and one-off. There is no common institutional framework. Early adopters use AI tools without guidance; most staff have no defined institutional position on AI.

A professional development pathway exists for AI literacy. Teachers have been oriented to the school's AI policy. A shared framework governs when AI is appropriate and what transparency looks like with students. This has been communicated and is referenced in planning.

AI readiness is embedded in ongoing professional development — not a one-time event. Teachers can articulate the school's AI governance position, model responsible use for students, and escalate concerns through a clear pathway. Competency is tracked at the institutional level, not assumed.

No structured student AI literacy exists. AI use is addressed only through academic honesty policy language, if at all. Students have received no instruction on responsible use or risks.

Some classroom-level conversations about AI have occurred, initiated by individual teachers. Students have been told what they cannot do but have not been taught how to use AI responsibly or what the real risks are.

Students receive structured AI literacy instruction at appropriate grade levels covering: responsible use, AI limitations, data privacy implications, and school expectations. This is integrated into existing curriculum, not a standalone assembly.

AI literacy is sequenced across grade levels with increasing developmental sophistication. Students can articulate why AI governance matters, demonstrate responsible practices, and engage with AI ethics conversations appropriate to their stage. Outcomes are tracked.

No inventory of AI tools in use exists. Teachers and students adopt AI tools without any approval process. No assessment of data collection practices has occurred. Data privacy obligations are not applied to AI tool adoption.

Some awareness exists that AI tools carry data risks. A few tools may have been reviewed informally. No formal procurement or approval process is in place. Data privacy obligations are not consistently applied to AI tool adoption.

A defined approval process exists for AI tool adoption. There is a maintained inventory of currently approved tools. Data privacy implications are assessed before adoption. A named person is accountable for vendor compliance at the institutional level.

Vendor accountability is embedded in procurement as standard practice. The approved tool inventory is reviewed at defined intervals. Tools are retired when they fall out of compliance or scope. Data practices are communicated to staff, students, and parents. The school can demonstrate compliance if asked.

Academic honesty policy has not been updated to address AI. Assessment design has not changed. No consistent institutional response to AI-assisted academic dishonesty exists. Individual teachers are making their own calls without guidance.

AI has been added to academic honesty policy language, typically as a blanket prohibition. Teachers are making their own decisions on AI use in assessments without institutional guidance. Detection attempts are being made but applied inconsistently.

The school has a defined institutional position on AI and academic integrity — not just prohibition, but a framework for when AI assistance is permitted, under what conditions, and with what transparency requirements. Assessment guidance has been issued to staff. Enforcement is consistent.

Assessment design has been systematically reviewed with AI in mind. The academic integrity framework treats AI as a contextual tool, not a blanket threat. Teachers have the guidance to make pedagogically sound decisions. Students understand the reasoning, not just the rules. The framework is reviewed as AI capabilities evolve.

No senior leader has designated responsibility for AI governance. AI-related decisions are made reactively, often by IT or individual teachers. There is no escalation pathway for AI-related incidents or concerns.

Leadership is aware AI governance is needed but has not formalised accountability. AI conversations happen in leadership meetings sporadically. No leader has received structured AI governance orientation. Decisions are still largely reactive.

A senior leader has named accountability for AI governance. Leadership has received orientation on AI risks and governance obligations relevant to schools. There is a defined escalation pathway for AI-related incidents. AI governance appears on the school improvement or strategic plan.

Leadership oversight is proactive, not reactive. The school has a governance rhythm — regular reviews, defined triggers for policy updates. Leaders can make informed AI tool adoption decisions, respond to incidents with a clear protocol, and communicate the school's AI position to stakeholders with confidence. External regulatory and technological developments are monitored and factored into planning.